You drink tap water every day, right? Do you know who invented the filtering mechanism that makes water pure and clean?… Well, do you actually care?

Do you know that this mechanism is exactly the same in all the taps of all the houses of any country? Do you know that this specialized piece is the work of an engineer who does it just because? Can you imagine what could happen if this person had a bad day?

Let’s talk about the XZ Utils library and why it is not a good idea to depend on a single supplier and make them angry. Let’s talk about the XZ Utils library and its latest developer, Jia Tan.

Yes, open source software can offer a series of benefits in terms of prices (because it is actually “free”), transparency, collaboration and adaptability, but it also entails risks regarding the security and excessive trust that we place as users.

What happened?

On March 29, Red Hat, Inc. disclosed the vulnerability CVE-2024-3094, with a score of 10 on the Common Vulnerability Scoring System scale, and, therefore, a critical vulnerability, which compromised the affected SSH servers.

This vulnerability affected the XZ Utils package, which is a set of software tools that provide file compression and decompression using the LZMA/LZMA2 algorithm, and is included in major Linux distributions. Had it not been discovered, it could have been very serious, since it was a malicious backdoor code, which would grant unauthorized remote access to the affected systems through SSH.

The vulnerability began in version 5.6.0 of XZ, and would also affect version 5.6.1.

During the liblzma building process it would retrieve an existing camouflaged test file in the source code, later used to modify specific functions in the liblzma code. The result is a modified liblzma library, which can be used by any software linked to it, intercepting and modifying data interaction with the library.

This process of implementing a backdoor in XZ is the final part of a campaign that was extended over 2 years of operations, mainly of the HUMNIT type (human intelligence) by the user Jia Tan.

User Jia Tan created his Github account in 2021, making their first commit to the XZ repository on February 6, 2022. More recently, on February 16, 2024, a malicious file would be added under the name of “build-to-host.m4” in .gitignore, later incorporated together with the launch of the package, to finally on March 9, 2024 incorporate the hidden backdoor in two test files:

• tests/files/bad-3-corrupt_lzma2.xz
• tests/files/good-large_compressed.lzma

How was it detected?

The main person in charge of locating this issue is Andres Freund.

It is one of the most important software engineers at Microsoft, who was performing micro-benchmarking tasks. During testing, they noticed that sshd processes were using an unusual amount of CPU even though the sessions were not established.

After profiling sshd, they saw a lot of CPU time in the liblzma library. This in turn reminded them of a recent bizarre complaint from Valgrind about automated testing in PostgreSQL. This behavior could have been overlooked and not discovered, leading to a large security breach on Debian/Ubuntu SSH servers.

As Andres Freund himself claims, a series of coincidences were required to be able to find this vulnerability, it was a matter of luck to have found it.

What set off Freund’s alarms was a small delay of only 0.5 sec in the ssh connections, which although it seems very little, was what led him to investigate further and find the problem and the potential chaos that it may have generated.

This underscores the importance of monitoring software engineering and security practices. The good news is that, the vulnerability has been found in very early releases of the software, so in the real world it has had virtually no effect, thanks to the quick detection of this malicious code. But it makes us think about what could have happened, if it had not been detected in time. It is not the first nor will be the last. The advantage of Open Source is that this has been made public and the impact can be evaluated, in other cases where there is no such transparency, the impact can be more difficult to evaluate and therefore, remediation.

Reflection

After what happened, we are in the right position to highlight both positive and negative points related to the use of open source.

As positive points we can find transparency and collaboration between developers from all over the world. Having a watchful community, in charge of detecting and reporting possible security threats, and have flexibility and adaptability, since the nature of open source allows adapting and modifying the software according to specific needs.

As for the disadvantages, we find the vulnerability to malicious attacks, as is the case with the action of developers with malicious intentions. Users trust that the software does not contain malicious code, which can lead to a false sense of security. In addition, due to the number of existing contributions and the complexity of the software itself, it can be said that it is very difficult to exhaustively verify the code.

If we add to all of that the existence of libraries maintained by one person or a very small group of people, the risk of single point of failure is greater. In this case, that need or benefit of having more people contributing is what caused the problem.

In conclusion, while open source software can offer us a number of benefits in terms of transparency, collaboration and adaptability, it can also present disadvantages or challenges in terms of the security and trust we place in it as users.ing.

Talking about too many cybersecurity alerts is not talking about the story of Peter and the Wolf and how people end up ignoring false warnings, but about its great impact on security strategies and, above all, on the stress it causes to IT teams, which we know are increasingly reduced and must fulfill multiple tasks in their day to day. 

Alert Fatigue is a phenomenon in which excessive alerts desensitize the people in charge of responding to them, leading to missed or ignored alerts or, worse, delayed responses. IT security operations professionals are prone to this fatigue because systems are overloaded with data and may not classify alerts accurately.

1. Definición de Fatiga de Alertas y su impacto en la seguridad de la organización

Alert fatigue, in addition to overwhelming data to interpret, diverts attention from what is really important. To put it into perspective, deception is one of the oldest war tactics since the ancient Greeks: through deception, the enemy’s attention was diverted by giving the impression that an attack was taking place in one place, causing the enemy to concentrate its resources in that place so that it could attack on a different front. Taking this into an organization, cybercrime can actually cause and leverage IT staff fatigue to find security breaches. This cost could become considerable in business continuity and resource consumption (technology, time and human resources), as indicated by an article by Security Magazine on a survey of 800 IT professionals:

• 85% percent of information technology (IT) professionals say more than 20% of their cloud security alerts are false positives. The more alerts, the harder it becomes to identify which things are important and which ones are not.
• 59% of respondents receive more than 500 public cloud security alerts per day. Having to filter alerts wastes valuable time that could be used to fix or even prevent issues.
• More than 50% of respondents spend more than 20% of their time deciding which alerts need to be addressed first. Alert overload and false positive rates not only contribute to turnover, but also to the loss of critical alerts. 55% say their team overlooked critical alerts in the past due to ineffective prioritization of alerts, often weekly and even daily.

What happens is that the team in charge of reviewing the alerts becomes desensitized. By human nature, when we get a warning of every little thing, we get used to alerts being unimportant, so it is given less and less importance. This means finding the balance: we need to be aware of the state of our environment, but too many alerts can cause more damage than actually help, because they make it difficult to prioritize problems.

2. Causes of Alert Fatigue

Alert Fatigue is due to one or more of these causes:

2.1. False positives

These are situations where a security system mistakenly identifies a benign action or event as a threat or risk. They may be due to several factors, such as outdated threat signatures, poor (or overzealous) security settings, or limitations in detection algorithms.

2.2. Lack of context

Alerts must be interpreted, so if alert notifications do not have the proper context, it can be confusing and difficult to determine the severity of an alert. This leads to delayed responses.

2.3. Several security systems

Consolidation and correlation of alerts are difficult if there are several security systems working at the same time… and this gets worse when the volume of alerts with different levels of complexity grows.

2.4. Lack of filters and customization of cybersecurity alerts

If they are not defined and filtered, it may cause endless non-threatening or irrelevant notifications.

2.5. Unclear security policies and procedures

Poorly defined procedures become very problematic because they contribute to aggravating the problem.

2.6. Shortage of resources

It is not easy to have security professionals who know how to interpret and also manage a high volume of alerts, which leads to late responses.

The above tells us that correct management and alert policies are required, along with the appropriate monitoring tools to support IT staff.

3. Most common false positives

According to the Institute of Data, false positives faced by IT and security teams are:

3.1. False positives about network anomalies

These take place when network monitoring tools identify normal or harmless network activities as suspicious or malicious, such as false alerts for network scans, legitimate file sharing, or background system activities.

3.2. False malware positives

Antivirus software often identifies benign files or applications as potentially malicious. This can happen when a file shares similarities with known malware signatures or displays suspicious behavior. A cybersecurity false positive in this context can result in the blocking or quarantine of legitimate software, causing disruptions to normal operations.

3.3. False positives about user behavior

Security systems that monitor user activities can generate a cybersecurity false positive when an individual’s actions are flagged as abnormal or potentially malicious. Example: an employee who accesses confidential documents after working hours, generating a false positive in cybersecurity, even though it may be legitimate.

False positives can also be found in email security systems. For example, spam filters can misclassify legitimate emails as spam, causing important messages to end up in the spam folder. Can you imagine the impact of a vitally important email ending up in the Spam folder?

4. Consequences of Alert Fatigue

Alert Fatigue has consequences not only on the IT staff themselves but also on the organization:

4.1. False sense of security

Too many alerts can lead the IT team to think they are false positives, leaving out the actions that could be taken.

4.2. Late Response

Too many alerts overwhelm IT teams, preventing them from reacting in time to real and critical risks. This, in turn, causes costly remediation and even the need to allocate more staff to solve the problem that could have been avoided.

4.3. Regulatory non-compliance

Security breaches can lead to fines and penalties for the organization.

4.4. Reputational damage to the organization

A breach of the company’s security gets disclosed (and we’ve seen headlines in the news) and impacts its reputation. This can lead to loss of customer trust… and consequently less revenue.

4.5. IT staff work overload

If the staff in charge of monitoring alerts feel overwhelmed with notifications, they may experience increased job stress. This has been one of the causes of lower productivity and high staff turnover in the IT area.

4.6. Deterioration of morale

Team demotivation can cause them to disengage and become less productive.

5. How to avoid these Alert Fatigue problems?

If alerts are designed before they are implemented, they become useful and efficient alerts, in addition to saving a lot of time and, consequently, reducing alert fatigue.

5.1. Prioritize

The best way to get an effective alert is to use the “less is more” strategy. You have to think about the absolutely essential things first.

• What equipment is absolutely essential? Hardly anyone needs alerts on test equipment.
• What is the severity if a certain service does not work properly? High impact services should have the most aggressive alert (level 1, for example).
• What is the minimum that is needed to determine that a computer, process, or service is not working properly?
  Sometimes it is enough to monitor the connectivity of the device, some other times something more specific is needed, such as the status of a service.

Answering these questions will help us find out what the most important alerts are that we need to act on immediately.

5.2. Avoiding false positives

Sometimes it can be tricky to get alerts to only go off when there really is a problem. Setting thresholds correctly is a big part of the job, but more options are available. Pandora FMS has several tools to help avoid false positives:

Dynamic thresholds

They are very useful for adjusting the thresholds to the actual data. When you enable this feature in a module, Pandora FMS analyzes its data history, and automatically modifies the thresholds to capture data that is out of the ordinary.

• FF Thresholds: Sometimes the problem is not that you did not correctly define the alerts or thresholds, but that the metrics you use are not entirely reliable. Let’s say we are monitoring the availability of a device, but the connection to the network on which it is located is unstable (for example, a very saturated wireless network). This can cause data packets to be lost or even there are times when a ping fails to connect to the device despite being active and performing its function correctly. For those cases, Pandora FMS has the FF Threshold. By using this option you may configure some “tolerance” to the module before changing state. Thus, for example, the agent will report two consecutive critical data for the module to change into critical status.
• Use maintenance windows: Pandora FMS allows you to temporarily disable alerting and even event generation of a specific module or agent with the Quiet mode. With maintenance windows (Scheduled downtimes), this can be scheduled so that, for example, alerts do not trigger during X service updates in the early hours of Saturdays.

5.3. Improving alert processes

Once they have made sure that the alerts that are triggered are the necessary ones, and that they will only trigger when something really happens, you may greatly improve the process as follows:

• Automation: Alerting is not only used to send notifications; it can also be used to automate actions. Let’s imagine that you are monitoring an old service that sometimes becomes saturated, and when that happens, the way to recover it is to just restart it. With Pandora FMS you may configure the alert that monitors that service to try to restart it automatically. To do this, you just need to configure an alert command that, for example, makes an API call to the manager of said service to restart it.
• Alert escalation: Continuing with the previous example, with alert escalation you may make the first action performed by Pandora FMS, when the alert is triggered, to be the restart of the service. If in the next agent run, the module is still in critical state, you may configure the alert so that, for example, a ticket is created in Pandora ITSM.
• Alert thresholds: Alerts have an internal counter that indicates when configured actions should be triggered. Just by modifying the threshold of an alert you may go from having several emails a day warning you of the same problem to receiving one every two or three days.

This alert (executed daily) has three actions: at first, it is about restarting the service. If at the next alert execution, the module has not been recovered, an email is sent to the administrator, and if it has not yet been solved, a ticket is created in Pandora ITSM. If the alert remains triggered on the fourth run, a daily message will be sent through Slack to the group of operators.

5.4. Other ways to reduce the number of alerts

• Cascade Protection is an invaluable tool in setting up efficient alerting, by skipping triggering alerts from devices dependent on a parent device. With basic alerting, if you are monitoring a network that you access through a specific switch and this device has a problem, you will start receiving alerts for each computer on that network that you can no longer access. On the other hand, if you activate cascade protection on the agents of that network (indicating whether they depend on the switch), Pandora FMS will detect that the main equipment is down, and will skip the alert of all dependent equipment until the switch is operational again.
• Using services can help you not only reduce the number of alerts triggered, but also the number of alerts configured. If you have a cluster of 10 machines, it may not be very efficient to have an alert for each of them. Pandora FMS allows you to group agents and modules into Services, along with hierarchical structures in which you may decide the weight of each element and alert based on the general status.

5.5. Implement an Incident Response Plan

Incident response is the process of preparing for cybersecurity threats, detecting them as they arise, responding to quell them, or mitigating them. Organizations can manage threat intelligence and mitigation through incident response planning. It should be remembered that any organization is at risk of losing money, data, and reputation due to cybersecurity threats.

Incident response requires assembling a team of people from different departments within an organization, including organizational leaders, IT staff, and other areas involved in data control and compliance. The following is recommended:

• Plan how to analyze data and networks for potential threats and suspicious activity.
• Decide which incidents should be responded to first.
• Have a plan for data loss and finances.
• Comply with all applicable laws.
• Be prepared to submit data and documentation to the authorities after a violation.

Finally, a timely reminder: incident response became very important starting with GDPR with extremely strict rules on non-compliance reporting. If a specific breach needs to be reported, the company must be aware of it within 72 hours and report what happened to the appropriate authorities. A report of what happened should also be provided and an active plan to mitigate the damage should be presented. If a company does not have a predefined incident response plan, it will not be ready to submit such a report.

The GDPR also requires to know if the organization has adequate security measures in place. Companies can be heavily penalized if they are scrutinized after the breach and officials find that they did not have adequate security.

Conclusion

The high cost to both IT staff (constant turnover, burnout, stress, late decisions, etc.) and the organization (disruption of operations, security breaches and breaches, quite onerous penalties) is clear. While there is no one-size-fits-all solution to prevent over-alerting, we do recommend prioritizing alerts, avoiding false positives (dynamic and FF thresholds, maintenance windows), improving alerting processes, and an incident response plan, along with clear policies and procedures for responding to incidents, to ensure you find the right balance for your organization.

Today, many companies generate and store huge amounts of data. To give you an idea, decades ago, the size of the Internet was measured in Terabytes (TB) and now it is measured in Zettabytes (ZB). 

Relational databases were designed to meet the storage and information management needs of the time. Today we have a new scenario where social networks, IoT devices and Edge Computing generate millions of unstructured and highly variable data. Many modern applications require high performance to provide quick responses to user queries.

In relational DBMSs, an increase in data volume must be accompanied by improvements in hardware capacity. This technological challenge forced companies to look for more flexible and scalable solutions.

NoSQL databases have a distributed architecture that allows them to scale horizontally and handle continuous and fast data flows. This makes them a viable option in high-demand environments such as streaming platforms where data processing takes place in real time.

Given the interest in NoSQL databases in the current context, we believe it is essential to develop a user guide that helps developers understand and effectively use this technology. In this article we aim to clarify some basics about NoSQL, giving practical examples and providing recommendations on implementation and optimization to make the most of its advantages.

NoSQL data modeling

One of the biggest differences between relational and non-relational bases lies in the approach we took to data modeling.

NoSQL databases do not follow a rigid and predefined scheme. This allows developers to freely choose the data model based on the features of the project.

The fundamental goal is to improve query performance, getting rid of the need to structure information in complex tables. Thus, NoSQL supports a wide variety of denormalized data such as JSON documents, key values, columns, and graph relationships.

Each NoSQL database type is optimized for easy access, query, and modification of a specific class of data. The main ones are:

• Key-value: Redis, Riak or DyamoDB. These are the simplest NoSQL databases. They store the information as if it were a dictionary based on key-value pairs, where each value is associated with a unique key. They were designed to scale quickly ensuring system performance and data availability.
• Documentary: MongoDB, Couchbase. Data is stored in documents such as JSON, BSON or XML. Some consider them an upper echelon of key-value systems since they allow encapsulating key-value pairs in more complex structures for advanced queries.
• Column-oriented: BigTable, Cassandra, HBase. Instead of storing data in rows like relational databases do, they do it in columns. These in turn are organized into logically ordered column families in the database. The system is optimized to work with large datasets and distributed workloads.
• Graph-oriented: Neo4J, InfiniteGraph. They save data as entities and relationships between entities. The entities are called “nodes” and the relationships that bind the nodes are the “edges”. They are perfect for managing data with complex relationships, such as social networks or applications with geospatial location.

NoSQL data storage and partitioning

Instead of making use of a monolithic and expensive architecture where all data is stored on a single server, NoSQL distributes the information on different servers known as “nodes” that join in a network called “cluster“.
This feature allows NoSQL DBMSs to scale horizontally and manage large volumes of data using partitioning techniques.

What is NoSQL database partitioning?

It is a process of breaking up a large database into smaller, easier-to-manage chunks.

It is necessary to clarify that data partitioning is not exclusive to NoSQL. SQL databases also support partitioning, but NoSQL systems have a native function called “auto-sharding” that automatically splits data, balancing the load between servers.

When to partition a NoSQL database?

There are several situations in which it is necessary to partition a NoSQL database:

• When the server is at the limit of its storage capacity or RAM.
• When you need to reduce latency. In this case you get to balance the workload on different cluster nodes to improve performance.
• When you wish to ensure data availability by initiating a replication procedure.

Although partitioning is used in large databases, you should not wait for the data volume to become excessive because in that case it could cause system overload.
Many programmers use AWS or Azure to simplify the process. These platforms offer a wide variety of cloud services that allow developers to skip the tasks related to database administration and focus on writing the code of their applications.

Partitioning techniques

There are different techniques for partitioning a distributed architecture database.

• Clustering
  It consists of grouping several servers so that they work together as if they were one. In a clustering environment, all nodes in the cluster share the workload to increase system throughput and fault tolerance.
• Separation of Reads and Writes
  It consists of directing read and write operations to different nodes in the cluster. For example, read operations can be directed to replica servers acting as children to ease the load on the parent node.
• Sharding
  Data is divided horizontally into smaller chunks called “shards” and distributed across different nodes in the cluster.
  It is the most widely used partitioning technique in databases with distributed architecture due to its scalability and ability to self-balance the system load, avoiding bottlenecks.
• Consistent Hashing
  It is an algorithm that is used to efficiently allocate data to nodes in a distributed environment.
  The idea of consistent hashes was introduced by David Karger in a research paper published in 1997 and entitled “Consistent Hashing and Random Trees: Distributed Caching Protocols for Relieving Hot Spots on the World Wide Web“.
  In this academic work, the “Consistent Hashing” algorithm was proposed for the first time as a solution to balance the workload of servers with distributed databases.
  It is a technique that is used in both partitioning and data replication, since it allows to solve problems common to both processes such as the redistribution of keys and resources when adding or removing nodes in a cluster.

  Nodes are represented in a circular ring and each data is assigned to a node using a hash function. When a new node is added to the system, the data is redistributed between the existing nodes and the new node.
  The hash works as a unique identifier so that when you make a query, you just have to locate that point on the ring.
  An example of a NoSQL database that uses “Consistent Hashing” is DynamoDB, since one of its strengths is incremental scaling, and to achieve this it needs a procedure capable of fractionating data dynamically.

Replication in NoSQL databases

It consists of creating copies of the data on multiple machines. This process seeks to improve database performance by distributing queries among different nodes. At the same time, it ensures that the information will continue to be available, even if the hardware fails.
The two main ways to perform data replication (in addition to the Consistent Hashing that we already mentioned in the previous section) are:

Master-slave server

Writing is made to the primary node and from there data is replicated to secondary nodes.

Peer to peer

All nodes in the cluster have the same hierarchical level and can accept writing. When data is written to one node it spreads to all the others. This ensures availability, but can also lead to inconsistencies if conflict resolution mechanisms are not implemented (for example, if two nodes try to write to the same location at the same time).

CAP theorem and consistency of NoSQL databases.

The CAP theorem was introduced by Professor Eric Brewer of the University of Berkeley in the year 2000. He explains that a distributed database can meet two of these three qualities at the same time:

• Consistency: All requests after the writing operation get the same value, regardless of where the queries are made.
• Availability: The database always responds to requests, even if a failure takes place.
• Partition Tolerance: The system continues to operate even if communication between some nodes is interrupted.

Under this scheme we could choose a DBMS that is consistent and partition tolerant (MongoDB, HBase), available and partition tolerant (DynamoDB, Cassandra), or consistent and available (MySQL), but all three features cannot be preserved at once.
Each development has its requirements and the CAP theorem helps us find the DBMS that best suits your needs. Sometimes it is imperative for data to be consistent at all times (for example, in a stock control system). In these cases, we usually work with a relational database. In NoSQL databases, consistency is not one hundred percent guaranteed, since changes must propagate between all nodes in the cluster.

BASIS and eventual consistency model in NoSQL

BASE is a concept opposed to the ACID properties (atomicity, consistency, isolation, durability) of relational databases. In this approach, we prioritize data availability over immediate consistency, which is especially important in applications that process data in real time.

The BASE acronym means:

• Basically Available: The database always sends a response, even if it contains errors if readings occur from nodes that did not yet receive the last writing.
• Soft state: The database may be in an inconsistent state when reading takes place, so you may get different results on different readings.
• Eventually Consistent: Database consistency is reached once the information has been propagated to all nodes. Up to that point we talk about an eventual consistency.

Even though the BASE approach arose in response to ACID, they are not exclusionary options. In fact, some NoSQL databases like MongoDB offer configurable consistency.

Tree indexing in NoSQL databases. What are the best-known structures?

So far we have seen how data is distributed and replicated in a NoSQL database, but we need to explain how it is structured efficiently to make its search and retrieval easier.
Trees are the most commonly used data structures. They organize nodes hierarchically starting from a root node, which is the first tree node; parent nodes, which are all those nodes that have at least one child; and child nodes, which complete the tree.
The number of levels of a tree determines its height. It is important to consider the final size of the tree and the number of nodes it contains, as this can influence query performance and data recovery time.
There are different tree indexes that you may use in NoSQL databases.

B Trees

They are balanced trees and perfect for distributed systems for their ability to maintain index consistency, although they can also be used in relational databases.
The main feature of B trees is that they can have several child nodes for each parent node, but they always keep their height balanced. This means that they have an identical or very similar number of levels in each tree branch, a particularity that makes it possible to handle insertions and deletions efficiently.
They are widely used in filing systems, where large data sets need to be accessed quickly.

T Trees

They are also balanced trees that can have a maximum of two or three child nodes.
Unlike B-trees, which are designed to make searches on large volumes of data easier, T-trees work best in applications where quick access to sorted data is needed.

AVL Trees

They are binary trees, which means that each parent node can have a maximum of two child nodes.
Another outstanding feature of AVL trees is that they are balanced in height. The self-balancing system serves to ensure that the tree does not grow in an uncontrolled manner, something that could harm the database performance.
They are a good choice for developing applications that require quick queries and logarithmic time insertion and deletion operations.

KD Trees

They are binary, balanced trees that organize data into multiple dimensions. A specific dimension is created at each tree level.
They are used in applications that work with geospatial data or scientific data.

Merkle Trees

They represent a special case of data structures in distributed systems. They are known for their utility in Blockchain to efficiently and securely encrypt data.
A Merkle tree is a type of binary tree that offers a first-rate solution to the data verification problem. Its creator was an American computer scientist and cryptographer named Ralph Merkle in 1979.
Merkle trees have a mathematical structure made up by hashes of several blocks of data that summarize all transactions in a block.

Data is grouped into larger datasets and related to the main nodes until all the data within the system is gathered. As a result, the Merkle Root is obtained.

How is the Merkle Root calculated?

1. The data is divided into blocks of a fixed size.

2. Each data block is subjected to a cryptographic hash function.

3. Hashes are grouped into pairs and a function is again applied to these pairs to generate their corresponding parent hashes until only one hash remains, which is the Merkle root.

The Merkle root is at the top of the tree and is the value that securely represents data integrity. This is because it is strongly related to all datasets and the hash that identifies each of them. Any changes to the original data will alter the Merkle Root. That way, you can make sure that the data has not been modified at any point.
This is why Merkle trees are frequently employed to verify the integrity of data blocks in Blockchain transactions.
NoSQL databases like Cassandra draw on these structures to validate data without sacrificing speed and performance.

Comparison between NoSQL database management systems

From what we have seen so far, NoSQL DBMSs are extraordinarily complex and varied. Each of them can adopt a different data model and present unique storage, consultation and scalability features. This range of options allows developers to select the most appropriate database for their project needs.
Below, we will give as an example two of the most widely used NoSQL DBMSs for the development of scalable and high-performance applications: MongoDB and Apache Cassandra.

MongoDB

It is a documentary DBMS developed by 10gen in 2007. It is open source and has been created in programming languages such as C++, C and JavaScript.

MongoDB is one of the most popular systems for distributed databases. Social networks such as LinkedIn, telecommunications companies such as Telefónica or news media such as the Washington Post use MongoDB.
Here are some of its main features.

• Database storage with MongoDB: MongoDB stores data in BSON files (binary JSON). Each database consists of a collection of documents. Once MongoDB is installed and Shell is running, you may create the DB just by indicating the name you wish to use. If the database does not already exist, MongoDB will automatically create it when adding the first collection. Similarly, a collection is created automatically when you store a file in it. You just have to add the first document and execute the “insert” statement and MongoDB will create an ID field assigning it an ObjectID value that is unique for each machine at the time the operation is executed.
• DB Partitioning with MongoDB: MongoDB makes it easy to distribute data across multiple servers using the automatic sharding feature. Data fragmentation takes place at the collection level, distributing documents among the different cluster nodes. To carry out this distribution, a “partition key” defined as a field is used in all collection documents. Data is fragmented into “chunks”, which have a default size of 64 MB and are stored in different shards within the cluster, ensuring that there is a balance. MongoBD monitors continuously chunk distribution among the shard nodes and, if necessary, performs automatic rebalancing to ensure that the workload supported by these nodes is balanced.
• DB Replication with MongoDB: MongoDB uses a replication system based on the master-slave architecture. The master server can perform writing and reading operations, but slave nodes only perform reads (replica set). Updates are communicated to slave nodes via an operation log called oplog.
• Database Queries with MongoDB: MongoDB has a powerful API that allows you to access and analyze data in real time, as well as perform ad-hoc queries, that is, direct queries on a database that are not predefined. This gives users the ability to perform custom searches, filter documents, and sort results by specific fields. To carry out these queries, MongoDB uses the “find” method on the desired collection or “findAndModify” to query and update the values of one or more fields simultaneously.
• DB Consistency with MongoDB: From version 4.0 (the most recent one is 6.0), MongoDB supports ACID transactions at document level. The “snapshot isolation” function provides a consistent view of the data and allows atomic operations to be performed on multiple documents within a single transaction. This feature is especially relevant for NoSQL databases, as it poses solutions to different consistency-related issues, such as concurrent writes or queries that return outdated file versions. In this respect, MongoDB comes very close to the stability of RDMSs.
• Database indexing with MongoDB: MongoDB uses B trees to index the data stored in its collections. This is a variant of the B trees with index nodes that contain keys and pointers to other nodes. These indexes store the value of a specific field, allowing data recovery and deletion operations to be more efficient.
• DB Security with MongoDB: MongoDB has a high level of security to ensure the confidentiality of stored data. It has several authentication mechanisms, role-based access configuration, data encryption at rest and the possibility of restricting access to certain IP addresses. In addition, it allows you to audit the activity of the system and keep a record of the operations carried out in the database.

Apache Cassandra

It is a column-oriented DBMS that was developed by Facebook to optimize searches within its platform. One of the creators of Cassandra is computer scientist Avinash Lakshman, who previously worked for Amazon, as part of the group of engineers who developed DynamoDB. For that reason, it does not come as a surprise that it shares some features with this other system.
In 2008 it was launched as an open source project, and in 2010 it became a top-level project of the Apache Foundation. Since then, Cassandra continued to grow to become one of the most popular NoSQL DBMSs.
Although Meta uses other technologies today, Cassandra is still part of its data infrastructure. Other companies that use it are Netflix, Apple or Ebay. In terms of scalability, it is considered one of the best NoSQL databases.

Let’s take a look at some of its key properties:

• Database storage with Apache Cassandra: Cassandra uses a “Column Family” data model, which is similar to relational databases, but more flexible. It does not refer to a hierarchical structure of columns that contain other columns, but rather to a collection of key-value pairs, where the key identifies a row and the value is a set of columns. It is designed to store large amounts of data and perform more efficient writing and reading operations.
• DB Partitioning with Apache Cassandra: For data distribution, Cassandra uses a partitioner that distributes data to different cluster nodes. This partitioner uses the algorithm “consistent hashing” to assign a unique partition key to each data row. Data possessing the same partition key will stay together on the same nodes. It also supports virtual nodes (vnodes), which means that the same physical node may have multiple data ranges.
• DB Replication with Apache Cassandra: Cassandra proposes a replication model based on Peer to peer in which all cluster nodes accept reads and writes. By not relying on a master node to process requests, the chance of a bottleneck occurring is minimal. Nodes communicate with each other and share data using a gossiping protocol.
• DB Queries with Apache Cassandra: Like MongoDB, Cassandra also supports ad-hoc queries, but these tend to be more efficient if they are based on the primary key. In addition, it has its own query language called CQL (Cassandra Query Language) with a syntax similar to that of SQL, but instead of using joins, it takes its chances on data denormalization.
• DB Indexation with Apache Cassandra: Cassandra uses secondary indexes to allow efficient queries on columns that are not part of the primary key. These indices may affect individual columns or multiple columns (SSTable Attached Secondary Index). They are created to allow complex range, prefix or text search queries in a large number of columns.
• DB Coherence with Apache Cassandra: By using Peer to Peer architecture, Cassandra plays with eventual consistency. Data is propagated asynchronously across multiple nodes. This means that, for a short period of time, there may be discrepancies between the different replicas. However, Cassandra also provides mechanisms for setting the consistency level. When a conflict takes place (for example, if the replicas have different versions), use the timestamp and validate the most recent version. In addition, perform automatic repairs to maintain data consistency and integrity if hardware failures or other events that may cause discrepancies between replicas take place.
• DB Security with Apache Cassandra: To use Cassandra in a safe environment, it is necessary to perform configurations, since many options are not enabled by default. For example, activate the authentication system and set permissions for each user role. In addition, it is critical to encrypt data in transit and at rest. For communication between the nodes and the client, data in transit can be encrypted using SSL/TLS.

Challenges in managing NoSQL databases. How does Pandora FMS help?

NoSQL DBMSs offer developers the ability to manage large volumes of data and scale horizontally by adding multiple nodes to a cluster.
To manage these distributed infrastructures, it is necessary to master different data partitioning and replication techniques (for example, we have seen that MongoDB uses a master-slave architecture, while Cassandra prioritizes availability with the Peer to peermodel).
Unlike RDMS, which share many similarities, in NoSQL databases there is no common paradigm and each system has its own APIs, languages and a different implementation, so getting used to working with each of them can be a real challenge.
Considering that monitoring is a fundamental component for managing any database, we must be pragmatic and rely on those resources that make our lives easier.
Both MongoDB and Apache Cassandra have commands that return system status information and allow problems to be diagnosed before they become critical failures. Another possibility is to use Pandora FMS software to simplify the whole process.

How to do so?

If this is a database in MongoDB, download Pandora FMS plugin for MongoDB. This plugin uses the mongostat command to collect basic information about system performance. Once the relevant metrics are obtained, they are sent to Pandora FMS data server for their analysis.
On the other hand, if the database works with Apache Cassandra, download the corresponding plugin for this system. This plugin obtains the information by internally running the tool nodetool, which is already included in the standard Cassandra installation, and offers a wide range of commands to monitor server status. Once the results are analyzed, the plugin structures the data in XML format and sends it to Pandora FMS server for further analysis and display.
For these plugins to work properly, copy the files to the plugin directory of Pandora FMS agent, edit the configuration file and, finally, restart the system (the linked articles explain the procedure very well).
Once the plugins are active, you will be able to monitor the activity of the cluster nodes in a graph view and receive alerts should any failures take place. These and other automation options help us save considerable time and resources in maintaining NoSQL databases.

Create a free account and discover all Pandora FMS utilities to boost your digital project!

And if you have doubts about the difference between NoSQL and SQL you can consult our post “NoSQL vs SQL: main differences and when to choose each of them“.

Today, digital trust is required inside and outside the organization, so tools must be implemented, with cybersecurity methods and best practices in each layer of your systems and their infrastructure: applications, operating systems, users, both on-premise and in the cloud. This is what we call System Hardening an essential practice that lays the foundation for a safe IT infrastructure. Its goal is to reduce the attack surface as much as possible, strengthening the systems to be able to face possible security attacks and get rid of as many entry points for cybercrime as possible.

Comprehensive Approach to Organizational Security

To implement organizational security, a comprehensive approach is undoubtedly required, since devices (endpoints, sensors, IoT), hardware, software, local environments, cloud (and hybrid) environments must be considered, along with security policies and local and even international regulatory compliance. It should be remembered that today and in the future we must not only protect an organization’s digital assets, but also avoid downtime and possible regulatory sanctions (associated with non-compliance with GDPR and data protection laws). Hardening also helps lay the solid foundation on which to implement advanced security solutions. Later, in Types of Hardening we will see where it is possible to implement security strengthening.

Benefits of Hardening in Cybersecurity

• Improved system functionality: Hardening measures help optimize system resources, eliminate unnecessary services and software, and apply security patches and updates. The consequences of actions lead to better system performance, as fewer resources are also wasted on unused or vulnerable components.
• Increased security level: A strengthened system reduces the surface area of a potential attack and strengthens defenses against threats (e.g., malware, unauthorized access, and data breaches). Confidential information is protected and user privacy is guaranteed.
• Compliance simplification and auditing: Organizations must comply with industry-specific security standards and regulations to protect sensitive data. Hardening helps meet these requirements and ensures compliance with industry-specific standards, such as GDPR (personal data protection), the payment card industry’s data security standard (PCI DSS) or the Health Insurance Portability and Accountability Acts (HIPAA, to protect a health insurance user’s data).

Other benefits include ensuring business continuity (without disruption or frictions), multi-layered defense (access controls, encryption, firewalls, intrusion detection systems, and regular security audits), and the ability to take a more proactive stance on security, with regular assessments and updates to prepare for emerging threats and vulnerabilities.
Every safe system must have been previously secured, and this is precisely what hardening consists of.

Types of Hardening

In the IT infrastructure set, there are several subsets that require different security approaches:

1. Configuration Management Hardening

Implementing and configuring security for multiple system components (including hardware, operating systems, and software applications). It also involves disabling unnecessary services and protocols, configuring access controls, implementing encryption, and safe communication protocols. It’s worth mentioning that security and IT teams often keep conflicting agendas. The hardening policy should take into account discussions between the two parties. It is also recommended to implement:

• Configurable item assessment: From user accounts and logins, server components and subsystems, what software and application updates and vulnerabilities to perform, networks and firewalls, remote access and log management, etc.
• Finding the balance between security and features: Hardening’s policy should consider both the requirements of the security team and the ability of the IT team to implement it using currently assigned levels of time and manpower. It must also be decided which challenges must be faced and which are not worthwhile for operational times and costs.
• Change management and “configuration drift” prevention: In Hardening, continuous monitoring must be implemented, where automation tools contribute to compliance with requirements at any time, getting rid of the need for constant scanning. Also, in unwanted changes, hardening policies that can happen in the production environment can be reinforced. Finally, in case of unauthorized changes, automation tools help detect anomalies and attacks to implement preventive actions.

2. Application Hardening

Protection of software applications running on the system, by removing or disabling unnecessary features, application-specific patching and security updates, along with safe coding practices and access controls, in addition to application-level authentication mechanisms. The importance of application security lies in the fact that users in the organization ask for safe and stable environments; on the part of the staff, patch and update application allows them to react to threats and implement preventive measures. Remember that users are often the entry point into the organization for cybercrime. Among the most common techniques, we can highlight:

• Install applications only from trusted repositories.
• Patch automations of standard and third-party applications.
• Installation of firewalls, antivirus and malware or spyware protection programs.
• Software-based data encryption.
• Password management and encryption applications.

3. Operating System (OS) Hardening

Configuring the operating system to minimize vulnerabilities, either by disabling unnecessary services, shutting down unused ports, implementing firewalls and intrusion detection systems, enforcing strong password policies, and regularly applying security patches and updates. Among the most recommended methods, there are the following:

• Applying the latest updates released by the operating system developer.
• Enable built-in security features (Microsoft Defender or third-party Endpoint Protection platform software or EPP, Endpoint Detection Rate or EDR from third parties). This will perform a malware search on the system (Trojan horses, sniffer, password sniffers, remote control systems, etc.).
• Remove unnecessary drivers and update used ones.
• Delete software installed on the machine that is unnecessary.
• Enable secure boot.
• Restrict system access privileges.
• Use biometrics or authentication FIDO (Fast Identity Online) in addition to passwords.

Also, a strong password policy can be implemented, protect sensitive data with AES encryption or self-encrypting drives, firmware resiliency technologies, and/or multi-factor authentication.

4. Server Hardening

Removing vulnerabilities (also known as attack vectors) that a hacker could use to access the server. It focuses on securing data, ports, components and server functions, implementing security protocols at hardware, firmware and software level. The following is recommended:

• Patch and update your operating systems periodically.
• Update third-party software needed to run your servers according to industry security standards.
• Require users to create and maintain complex passwords consisting of letters, numbers, and special characters, and update these passwords frequently.
• Lock an account after a certain number of failed login attempts.
• Disable certain USB ports when a server is booted.
• Leverage multi-factor authentication (MFA)
• Using encryption AES or self-encrypted drives to hide and protect business-critical information.
• Use virus and firewall protection and other advanced security solutions.

5. Network Hardening

Protecting network infrastructure and communication channels. It involves configuring firewalls, implementing intrusion prevention systems (IPS) and intrusion detection systems (IDS), encryption protocols such as SSL/TLS, and segmenting the network to reduce the impact of a breach and implement strong network access controls. It is recommended to combine IPS and IDS systems, in addition to:

• Proper configuration of network firewalls.
• Audits of network rules and access privileges.
• Disable unnecessary network ports and network protocols.
• Disable unused network services and devices.
• Network traffic encryption.

It is worth mentioning that the implementation of robust monitoring and recording mechanisms is essential to strengthen our system. It involves setting up a security event log, monitoring system logs for suspicious activity, implementing intrusion detection systems, and conducting periodic security audits and reviews to identify and respond to potential threats in a timely manner.

Practical 9-Step Hardening Application

Although each organization has its particularities in business systems, there are general hardening tasks applicable to most systems. Below is a list of the most important tasks as a basic checklist:

1. Manage access: Ensure that the system is physically safe and that staff are informed about security procedures. Set up custom roles and strong passwords. Remove unnecessary users from the operating system and prevent the use of root or “superadmin” accounts with excessive privileges. Also, limit the membership of administrator groups: only grant elevated privileges when necessary.

2. Monitor network traffic: Install hardened systems behind a firewall or, if possible, isolated from public networks. A VPN or reverse proxy must be required to connect. Also, encrypt communications and establish firewall rules to restrict access to known IP ranges.

3. Patch vulnerabilities: Keep operating systems, browsers, and any other applications up to date and apply all security patches. It is recommended to keep track of vendor safety advisories and the latest CVEs.

4. Remove Unnecessary Software: Uninstall any unnecessary software and remove redundant operating system components. Unnecessary services and any unnecessary application components or functions that may expand the threat surface must be disabled.

5. Implement continuous monitoring: Periodically review logs for anomalous activity, with a focus on authentications, user access, and privilege escalation. Reflect records in a separate location to protect the integrity of records and prevent tampering. Conduct regular vulnerability and malware scans and, if possible, conduct an external audit or penetration test.

6. Implement secure communications: Secure data transfer using safe encryption. Close all but essential network ports and disable unsafe protocols such as SMBv1, Telnet, and HTTP.

7. Performs periodic backups: Hardened systems are, by definition, sensitive resources and should be backed up periodically using the 3-2-1 rule (three copies of the backup, on two types of media, with one copy stored off-site).

8. Strengthen remote sessions: If you must allow Secure Shell or SSH (remote administration protocol), make sure a safe password or certificate is used. The default port must be avoided, in addition to disabling elevated privileges for SSH access. Monitor SSH records to identify anomalous uses or privilege escalation.

9. Monitor important metrics for security:Monitor logs, accesses, number of connections, service load (CPU, Memory), disk growth. All these metrics and many more are important to find out if you are being subjected to an attack. Having them monitored and known in real time can free you from many attacks or service degradations.

Hardening on Pandora FMS

Pandora FMS incorporates a series of specific features to monitor server hardening, both Linux and Windows. For that, it runs a special plugin that will perform a series of checks, scoring whether or not it passes the registration. These checks are scheduled to run from time to time. The graphical interface structures what is found in different categories, and the evolution of system security over time can be visually analyzed, as a temporal graph. In addition, detailed technical reports can be generated for each machine, by groups or made comparative.

It is important to approach the security tasks of the systems in a methodical and organized way, attending first to the most critical and being methodical, in order to be able to do it in all systems equally. One of the fundamental pillars of computer security is the fact of not leaving cracks, if there is an entrance door, however small it may be, and as much as we secured the rest of the machines, it may be enough to have an intrusion in our systems.

The Center for Internet Security (CIS) leads the development of international hardening standards and publishes security guidelines to improve cybersecurity controls. Pandora FMS uses the recommendations of the CIS to implement a security audit system, integrated with monitoring to observe the evolution of Hardening throughout your organization, system by system.

Use of CIS Categories for Safety Checks

There are more than 1500 individual checks to ensure the security of systems managed by Pandora FMS. Next, we mention the CIS categories audited by Pandora FMS and some recommendations:

• Hardware and software asset inventory and control
  It refers to all devices and software in your organization. Keeping an up-to-date inventory of your technology assets and using authentication to block unauthorized processes is recommended.
• Device inventory and control
  It refers to identifying and managing your hardware devices so that only those who are authorized have access to systems. To do this, you have to maintain adequate inventory, minimize internal risks, organize your environment and provide clarity to your network.
• Vulnerability Management
  Continuously scanning assets for potential vulnerabilities and remediating them before they become the gateway to an attack. Patch updating and security measures in the software and operating systems must be ensured.
• Controlled use of administrative privileges
  It consists of monitoring access controls and user performance with privileged accounts to prevent any unauthorized access to critical systems. It must be ensured that only authorized people have elevated privileges to avoid any misuse of administrative privileges.
• Safe hardware and software configuration
  Security configuration and maintenance based on standards approved by your organization. A rigorous configuration management system should be created, to detect and alert about any misconfigurations, along with a change control process to prevent attackers from taking advantage of vulnerable services and configurations.
• Maintenance, supervision and analysis of audit logs and records
  Collection, administration and analysis of event audit logs to identify possible anomalies. Detailed logs are required to fully understand attacks and to be able to effectively respond to security incidents.
• Defenses against malware
  Supervision and control of installation and execution of malicious code at multiple points in the organization to prevent attacks. Anti-malware software should be configured and used and take advantage of automation to ensure quick defense updates and swift corrective action in the event of attacks.
• Email and Web Browser Protection
  Protecting and managing your web browsers and email systems against online threats to reduce the attack surface. Deactivate unauthorized email add-ons and ensure that users only access trusted websites using network-based URL filters. Remember to keep these most common gateways safe from attacks.
• Data recovery capabilities
  Processes and tools to ensure your organization’s critical information is adequately supported. Make sure you have a reliable data recovery system in place to restore information in the event of attacks that compromise critical data.
• Boundary defense and data protection
  Identification and classification of sensitive data, along with a number of processes including encryption, data leak protection plans, and data loss prevention techniques. It establishes strong barriers to prevent unauthorized access.
• Account Monitoring and Control
  Monitor the entire lifecycle of your systems and application accounts, from creation through use and inactivity to deletion. This active management prevents attackers from taking advantage of legitimate but inactive user accounts for malicious purposes and allows them to maintain constant control over the accounts and their activities.
  It is worth mentioning that not all categories are applicable in a system, but there are controls to verify whether or not they apply. Let’s look at some screens as an example of display.

Detail example in a hardening control of a Linux (Debian) server

This control explains that it is advisable to disable the ICMP packet forwarding, as contemplated in the recommendations of CIS, PCI_DSS, NIST and TSC.

Example listing of checks by group (in this case, network security)

Example of controls, by category on a server:

The separation of the controls by category is key to be able to organize the work and to delimit the scope, for example, there will be systems not exposed to the network where you may “ignore” the network category, or systems without users, where you may avoid user control.

Example of the evolution of the hardening of a system over time:

This allows you to see the evolution of securitization in a system (or in a group of systems). Securitization is not an easy process, since there are dozens of changes, so it is important to address it in a gradual way, that is, planning their correction in stages, this should produce a trend over time, like the one you may see in the attached image. Pandora FMS is a useful tool not only for auditing, but also for monitoring the system securitization process.

Other additional safety measures related to hardening

• Permanent vulnerability monitoring. Pandora FMS also integrates a continuous vulnerability detection system, based on mitre databases (CVE, Common Vulnerabilities and Exposure) and NIST to continuously audit vulnerable software across your organization. Both the agents and the remote Discovery component are used to determine on which of your systems there is software with vulnerabilities. More information here.
• Flexibility in inventory: Whether you use Linux systems from different distributions or any Windows version, the important thing is to know and map our infrastructure well: installed software, users, paths, addresses, IP, hardware, disks, etc. Security cannot be guaranteed if you do not have a detailed inventory.
• Constant monitoring of security infrastructure: It is important to monitor the status of specific security infrastructures, such as backups, antivirus, VPN, firewalls, IDs/IPS, SIEM, honeypots, authentication systems, storage systems, log collection, etc.
• Permanent monitoring of server security: Verifying in real time the security of remote access, passwords, open ports and changes to key system files.
• Proactive alerts: Not only do we help you spot potential security breaches, but we also provide proactive alerts and recommendations to address any issues before they become a real threat.

I invite you to watch this video about Hardening on Pandora FMS

Positive impact on safety and operability

As we have seen, hardening is part of the efforts to ensure business continuity. A proactive stance on server protection must be taken, prioritizing risks identified in the technological environment and applying changes gradually and logically. Patches and updates must be applied constantly as a priority, relying on automated monitoring and management tools that ensure the fast correction of possible vulnerabilities. It is also recommended to follow the best practices specific to each hardening area in order to guarantee the security of the whole technological infrastructure with a comprehensive approach.

Additional Resources

Links to Pandora FMS documentation or read the references to CIS security guidelines: See interview with Alexander Twaradze, Pandora FMS representative to countries implementing CIS standards.

Pandora FMS team

Pandora FMS’s editorial team is made up of a group of writers and IT professionals with one thing in common: their passion for computer system monitoring. Pandora FMS’s editorial team is made up of a group of writers and IT professionals with one thing in common: their passion for computer system monitoring.

From the computer, we increasingly perform different tasks simultaneously (listening to music while writing a report, receiving files by email and downloading videos), which involve executing commands, and sending and receiving data. Over time, computer performance can suffer if CPU usage is not optimized.

But what is a CPU?

CPU stands for central processing unit. The CPU itself is the brain of a computer, on which most calculations and processes are performed. The two components of a CPU are:

• The arithmetic logic unit (ALU), which performs arithmetic and logical operations.
• The Control Unit (CU), which retrieves instructions from the memory, decodes and executes them, calling the ALU when necessary.

In this diagram you may see that the CPU also contains the memory unit, which contains the following elements:

• The ROM (Read Only Memory): It is a read-only memory; that is, you may only read the programs and data stored in it. It is also a primary memory unit of the computer system, and contains some electronic fuses that can be programmed for specific information. The information is stored in ROM in binary format. It is also known as permanent memory.
• The RAM (Random Access Memory): As its name suggests, it is a type of computer memory that can be accessed randomly, any byte of memory without handling the previous bytes. RAM is a high-speed component on devices that temporarily stores all the information a device needs.
• Cache: The cache stores data and allows quick access to it. Cache speed and capacity improves device performance.

Its crucial role in the computer operation

By its components, the speed and performance of a computer are directly related to the CPU features, such as:

• Energy consumption. It refers to the amount of power that the CPU consumes when executing actions, the higher the quality, the higher the power consumption.
• The clock frequency. It refers to the clock speed that the CPU has and that determines the number of actions it can execute in a period of time.
• The number of cores. The greater the number of cores, the greater the number of actions that can be performed simultaneously.
• The number of threads. It helps the processor handle and execute actions more efficiently. It splits tasks or processes to optimize waiting times between actions.
• Cache memory. It stores data and allows quick access to it.
• The type of bus. It refers to the communication that the CPU establishes with the rest of the system.

Relationship between CPU speed/power and computer performance

Impact of speed and power on system effectiveness.

CPUs are classified by the number of cores:

• De un solo núcleo, en el que el procesador sólo puede realizar una acción a la vez, es el procesador más antiguo.
• Two-core, which allows you to perform more than one action at a time.
• Four cores, separate from each other, which allows them to perform several actions at once and are much more efficient.

Considering this, we understand why current CPUs have two or more cores to be able to perform several operations at the same time or balance the load so that the processor does not become 100% busy, which would prevent performing some operations.

Consequences of a slow or overloaded CPU

When a CPU is overloaded, the consequences are as follows, and in the indicated order:

• Loss of performance, encouraging task processing.
• Overheating of the computer, a sign that the components receive more demand than the capacity they have.
• If the temperature of a processor exceeds its limit, it slows down and can even lead to a total system shutdown.

With this, if you do not want to reach the last consequence that puts your equipment at risk, the CPU load must be optimized.

Importance of Reducing CPU Usage

Benefits of optimizing CPU load

When CPU consumption is minimized, the benefits become noticeable in:

• Energy savings: Lower power consumption, avoiding unnecessary use of processor resources.
• Battery life: It extends battery life by reducing power consumption.
• Higher performance: Performance improvements at all times.
• Lower processor overheating and exhaustion.
• Lower environmental impact: With lower energy consumption, the carbon footprint of the organization is reduced and it is possible to contribute to ESG goals (Environment, Social, Governance).

Monitoring CPU usage in IT environments

Role of IT support service agents

To give continuity to the business, it is always necessary to supervise systems and equipment to ensure service delivery without interruptions or events that may put the company at risk. IT support agents precisely provide face-to-face or remote support at:

• Install and configure equipment, operating systems, programs and applications.
• Regularly maintain equipment and systems.
• Support employees on technology use or needs.
• Detect risks and problems in equipment and systems, and take action to prevent or correct them.
• Perform diagnostics on hardware and software operation.
• Replace parts or the whole equipment when necessary.
• Make and analyze reports on the state of equipment and systems.
• Order parts and spare parts, and, if possible, schedule inventories.
• Provide guidance on the execution of new equipment, applications or operating systems.
• Test and evaluate systems and equipment prior to implementation.
• Configure profiles and access to networks and equipment.
• Carry out security checks on all equipment and systems.

Remote monitoring and management (RMM) tools for effective monitoring.

In order to carry out the functions of the technical support service agent, there are tools for remote monitoring and management. Remote Monitoring and Management (RMM) is software that helps run and automate IT tasks such as updates and patch management, device health checks, and network monitoring. The approach of RMM, of great support for internal IT teams as well as for Managed Service Providers (MSPs), is to centralize the support management process remotely, from tracking devices, knowing their status, to performing routine maintenance and solving problems that arise in equipment and systems. This becomes valuable considering that IT services and resources are in hybrid environments, especially to support the demand of users who not only work in the office but those who are working remotely. Tracking or maintaining resources manually is literally impossible.
To learn more about RMM, visit this Pandora FMS blog: What is RMM software?

Tips for reducing CPU usage on Chromebooks and Windows

Closing tabs or unnecessary applications

This is one of the easiest methods to reduce CPU usage. Close any tabs or apps you’re not using in your web browser. This frees up resources on your computer, allowing you to perform other tasks.
To open the Task Manager on a Chromebook, press “Ctrl” + “Shift” + “T”.
Right-click on the Windows taskbar and select “Task Manager”.
In Task Manager, close any tabs or apps you’re no longer using.

Disabling non-essential animations or effects

Some animations and effects can take up large CPU resources, so it’s best to disable them. First go to system settings and look for an option called “Performance” or “Graphics”, from which you may turn off animations and effects.
On Chromebook, go to Settings > Advanced > Performance and turn off any unnecessary animation or effects.
In Windows, go to Dashboards > System & Security > Performance and turn off unnecessary animations or effects.

Driver update

Outdated drivers can degrade computer performance, leading to excessive CPU usage. To update your drivers, visit your computer manufacturer’s website and download the latest drivers for your hardware. Install and then restart your computer.

Hard drive defragmentation

Over time, the hard drive can fragment, affecting computer performance. Open the “Disk Defragmenter” tool from the Start menu to defragment it. Select “Disk Defragmenter” from the Start menu. Restart the computer after defragmenting the hard drive.

Malware scanning

Malware is malicious software that aims to cause damage to systems and computers. Sometimes malware can take up CPU resources, so it’s key to scan your computer and perform a scan on a regular basis to find malware. For that, use a trusted antivirus program. Once the scan is complete, remove any malware that may have been detected.

System restoration

If you are experiencing high CPU usage, you may try performing a system restore. It can be a drastic solution, but it will return the computer to a previous state where it worked normally. To do this, open the Start menu and search for “System Restore”.
Click the “Start” button and type “System Restore”.
Choose a restore point that was created before you started experiencing problems with high CPU usage. Restart the computer.

Software update

Outdated software also causes performance issues on your computer, including high CPU usage. To update the software, open the Control Panel and go to the “Windows Update” settings, check for updates and install those that are available.
In addition to these tips, it is recommended to use RMM tools and agents installed on the company’s computers, servers, workstations and devices, which run in the background in order to collect information on network activity, performance and system security in real time. Through its analysis, it is possible to detect patterns and anomalies to generate support tickets (and scale them if necessary according to their severity) or, ideally, act preventively.
Proactive monitoring by internal IT teams or MSP providers is also recommended to ensure a stable and safe IT environment for users. Importantly, proactivity reduces the costs associated with equipment repair and data recovery.

Advanced Optimization: Overclocking and CPU Switching

Explanation of advanced options such as overclocking

overclocking is a technique used to increase clock frequency of an electronic component, such as the CPU (processor) or the GPU (graphics card), beyond the specifications set by the equipment manufacturer. That is, overlocking tries to force the component to operate at a higher speed than it originally offers.

Considerations on installing a new CPU

While it may seem like a simple matter to install a new CPU, there are considerations for installing a new CPU to ensure your computer’s performance. It is recommended to have the following at hand:

• A screwdriver: Depending on your PC and the content that is installed on it, you may need one or more screwdrivers to remove the screws from your CPU and even the motherboard, in case you need to remove it.
• Thermal paste: This is a must when installing a new CPU, especially if you do not have a CPU cooler with pre-applied thermal paste.
• Isopropyl alcohol wipes: You will need them to clean the residual thermal paste of the processor and the contact point of the CPU cooler. You may even use isopropyl alcohol along with some very absorbent paper towels.
• Antistatic Wristband: Since fragile and expensive components such as the CPU, motherboard and cooler will be worked on, we suggest using an antistatic wristband to protect the components from static discharges.

With this at hand, we now let you know three important considerations:

• Take static precautions:
  The CPU is sensitive to static discharges. Its pins are delicate and work at high temperatures, so you have to take precautions. It is recommended to wear an antistatic bracelet or take a metal surface to “unload” yourself. In case the CPU has been used in another machine or if the fan is being replaced, you may need to remove the old thermal compound with isopropyl alcohol (not on the CPU contacts). There is no need to remove the battery from the motherboard during CPU installation. This would cause saved BIOS configurations to be lost. A minimum force must be required to lock the CPU charging lever in place.
• Motherboard compatibility:
  It is important to check the documentation of your motherboard to know the type of socket that is used. Remember that AMD and Intel use different sockets, so you can’t install an Intel processor on an AMD board (and vice versa). If you can’t find this information, you may use the CPU-Z program to determine the type of socket to use.
• Correct location and alignment:
  The CPU must be properly placed in the socket. If you do not do it correctly, the CPU will not work. You should make sure to properly install the fan and heat sink to avoid temperature problems.

In a nutshell…

The demand for resources on our computers to be able to process multiple tasks simultaneously has made it clear why attention should be paid to using the CPU with speed and power. For that reason, remote supervision and management tools are a resource for IT employees (or Managed Service Provider) in order to be able to know from a central point the status of systems and equipment and undertake maintenance and prevention actions remotely, such as driver updates, malware scanning, software updates, among others. The results of these efforts will be energy savings, increased performance, and extended battery life, along with reduced processor overheating and reduced environmental impact.