Here are some of the top Kubernetes blogs and websites worth reading:

1. Kubernetes.io: The official Kubernetes blog is a great place to start your Kubernetes journey. It provides a wealth of information on Kubernetes architecture, installation, administration, and development. You can also find Kubernetes documentation, tutorials, and case studies.
2. The New Stack: The New Stack is a leading platform for DevOps and cloud-native computing news, analysis, and events. Its Kubernetes coverage is comprehensive and includes articles, podcasts, and videos. The New Stack is also home to KubeCon + CloudNativeCon, the largest Kubernetes conference in the world.
3. Red Hat Blog: Red Hat is a leading provider of open-source software solutions, including Kubernetes. Its blog provides valuable insights into Kubernetes deployment, management, security, and performance. You can also find Kubernetes-related news, trends, and best practices.
4. Rancher Labs Blog: Rancher Labs is a provider of Kubernetes management solutions. Its blog offers practical tips and advice on Kubernetes deployment, administration, and optimization. You can also find Rancher Labs’ Kubernetes-related products and services.
5. Weaveworks Blog: Weaveworks is a provider of Kubernetes observability and networking solutions. Its blog focuses on Kubernetes best practices, use cases, and trends. You can also find Weaveworks’ Kubernetes-related products and services.
6. CNCF Blog: The Cloud Native Computing Foundation (CNCF) is the home of Kubernetes and other cloud-native projects. Its blog provides updates and insights into Kubernetes and other CNCF projects. You can also find information on CNCF events and initiatives.
7. Kubernetes Podcast: The Kubernetes Podcast is a weekly show hosted by Craig Box and Adam Glick. It features Kubernetes experts discussing Kubernetes news, use cases, and best practices. You can also find interviews with Kubernetes users and vendors.

These are just a few of the many Kubernetes blogs and websites out there. Whether you’re a beginner or an advanced Kubernetes user, you’ll find valuable insights and knowledge from these sources. Happy reading!

Bonus: 5 Best Kubernetes Books for Beginners

Сообщение Expert Insights: 7 Kubernetes Blogs and Websites You Need to Know появились сначала на Acure AIOps Platform.

After reading these books, you’ll be able to deploy and manage large-scale containers within your organization. The books cover both basic and advanced Kubernetes concepts.

Here Are 5 Books Every Kubernetes Beginner Should Read

• “Kubernetes: Up and Running, 2nd Edition” by Kelsey Hightower, Brendan Burns, and Joe Beda: This book provides an excellent introduction to Kubernetes, covering the basic concepts and principles. It includes hands-on experience through practical examples and exercises.
• “Learning Kubernetes: A Guide to Running Containerized Applications” by Joaquín Menchaca: This book offers a comprehensive overview of Kubernetes, including the architecture, components, and API objects. It also covers the basics of deploying and managing applications on Kubernetes.
• “Kubernetes in Action“ by Marko Luksa: This practical guide covers the key concepts and techniques for deploying and managing containerized applications on Kubernetes. It includes practical examples and exercises to help beginners learn Kubernetes.
• “Kubernetes: The Complete Guide To Master Kubernetes (March 2022)“ by Eric Keller: This book covers Kubernetes basics and provides a comprehensive guide to deploying and managing applications on Kubernetes. It includes practical examples and exercises to help beginners learn Kubernetes.
• “The Kubernetes Book” by Nigel Poulton: This comprehensive guide covers Kubernetes architecture, components, and API objects. It also covers the basics of deploying and managing applications on Kubernetes. It includes practical examples and exercises to help beginners learn Kubernetes.

Kubernetes has become the go-to choice for a cloud-native approach. With a thriving community, it currently dominates the container ecosystem. Any organization that wants to progress in its cloud-native journey must adopt Kubernetes. Having knowledge of Kubernetes is an added advantage for developers, SREs, architects, and DevOps professionals. The books listed above will significantly impact your Kubernetes learning curve and boost your confidence.

Read: 25 Kubernetes experts you should follow on Twitter

+ Bonus: Kubernetes Learning Courses for Beginners

• Kubecampus.io – Learn basic or advanced Kubernetes skills at your own pace, in an easy to follow format.
• Pluralsight.com – In this course, Getting Started with Kubernetes, you’ll learn the fundamentals of Kubernetes and the ‘Kubernetes way’. 
• Udemy.com – Kubernetes for the Absolute Beginners. Learn Kubernetes in simple, easy and fun way with hands-on coding exercises. For beginners in DevOps.
• Coursera.org – In this course, each module aims to build on your ability to interact with GKE, and includes hands-on labs for you to experience functionalities first-hand.
• KodekCloud.com – This course is for absolute Kubernetes beginners. With zero knowledge about Kubernetes, once you take this course and complete all of the hands-on coding exercises, you will be ready to deploy your own applications on a Kubernetes platform.

Subscribe to our newsletter to receive the latest updates, exclusive content, and special offers. Stay informed and never miss out on valuable insights and resources. Join our community and stay tuned for all the latest news and trends in your industry.

Сообщение 5 Best Kubernetes Books for Beginners появились сначала на Acure AIOps Platform.

Site reliability managers primarily focus on automating easy tasks within a system, enhancing system functionality/reducing error, and detecting/fixing problems. The job of an effective SRE is to ensure that systems function as smoothly as possible, eliminating extra work for IT teams and reducing the likelihood of system collapse. 

If you would like to learn more about becoming an SRE, the professionals at Acure have put together the following guide on SREs. We will break down the characteristics of an ideal SRE candidate, the general requirements for the job, and day-to-day SRE practices. Keep reading to find out more. 

Who Is SRE?

In the past, software development teams created programs without the help of IT teams. After the software teams successfully designed their systems, they pass their work onto an IT team. This IT team would then be responsible for fixing errors, taking calls, and maintaining and deploying the program.

A site reliability engineer is a position that Google created to streamline IT processes. This position is the bridge between IT operators and software developers, capitalizing upon the practices of DevOps. Where DevOps primarily focuses on ensuring that operation and developer teams work together to create reliable systems and develop products, SREs work to enhance system reliability and resilience.

SREs primarily monitor the following aspects of a system:

• Website Traffic
• System Errors
• Saturation/Capacity
• System Latency
• System Automation
• Incident Response

Read more about SRE principles and its benefits for organizations in our previous article.

Career and Salary

The average salary of an SRE in the United States is around $100,000 a year. It is also common for SREs to earn bonuses that amount to a little over $20,000 extra a year. The more experience you gain as an SRE, the more money you will make. 

Employers are more likely to hire candidates with a degree in computer science, though sufficient certifications and previous background in IT can guarantee you a position in a company. Some companies will allow you to work remotely, while others may require that you come into the office. Popular companies for SREs include Target, Twitter, Adobe, Wayfair, etc. 

Role and Responsibilities

The primary responsibilities of an SRE (or SRE teams) include:

• Fixing issues with a program/system
• Quickly responding to client problems
• Creating software to streamline processes for IT workers
• Managing on-call responsibilities
• Documenting their knowledge of systems and common errors
• Automating system administration
• Analyzing past problems to prevent future errors

SREs constantly look for new ways to improve systems and reduce common errors or incidents. If such a malfunction occurs, an SRE must address the error quickly. Then, the SRE ought to reflect on how they can prevent such an error from occurring in the future by enhancing the reliability of that system.

Many site reliability engineers use AI programs to streamline their job. Such programs sort through system issues to determine which alerts are important. These AI programs enhance the reliability of an SRE by ensuring that their IT services perform well without wasting time.

Skills, Courses, and Certification

People who are most suitable for a career in system reliability engineering must:

• Be quick on their feet
• Easily understand the basics of a system even if they have not seen it before
• Enjoy building complex software and systems
• Possess curiosity and a love for learning
• Stay calm despite feeling pressured

Beyond these characteristics, SREs must have some background in IT or software development. However, ideal candidates do not come from a specific discipline in IT. Anyone from a biochemist to a self-taught candidate for sysadmin can find success in a career as an SRE.

Suggested Courses and Skills for SREs

Having a background and/or certification in certain programs and coding is helpful when applying for site reliability engineer jobs. You should learn how to program shell scripts as well as understand programming languages such as C, Rust, Go, Python, and Java.

We also suggest that you learn how to create websites. To do so, either take a course or use cloud servers such as Amazon Web Services or Digital Ocean on your own time. Creating your website by coding your own HTML or using old-school programming methods such as PHP and MySQL can also help you become a better SRE.

Learning about automation through a continuous integration pipeline like Jenkins or Travis CI is also helpful. Furthermore, you should also know some basic code editing skills. Use programs such as Atom or Eclipse for coding practice.

You must also have a basic understanding of NoSQL databases and data models. Understanding Linux and service-oriented architecture (SOA) is also quite helpful. We also recommend you understand monitoring tools and software systems (such as Acure).

Though not all of these skills are necessary to become an SRE, they will help you succeed in your career.

Potential Online Courses

If you feel you have a sufficient background in coding, automation, programming languages, etc., reinforce your skills through online courses and other study materials. These certifications will help you get a feel for the SRE career path and make you a more attractive candidate to potential employers.

• Site Reliability Engineering Certification
• Tools, Automation, and Troubleshooting for SRE
• Automation for SRE
• Foundational Training for Site Reliability Engineering
• System Reliability in SRE

Further Enhancement of SRE Skills Through Acure

If becoming a site reliability engineer interests you, we highly recommend learning about products such as Acure. We provide an IT Ops tool that SRE managers use to ensure the smooth functioning of IT services, alerting SREs only when the error is pertinent. System reliability managers who use Acure must have prior knowledge of how the platform operates.

Check Acure documentation to be more advanced with Acure functionality and create Userpace to try it out!

Сообщение How to Become a Site Reliability Engineer? появились сначала на Acure AIOps Platform.

Metrics are an essential part of data monitoring. They are used to measure, track and analyze the performance of a system, process or activity. Metrics give us a more objective and accurate view of how a system, process or activity is performing, which helps us identify and address potential problems. Metrics provide a quantitative way of measuring progress and performance of a system, process or activity. They also help identify areas where improvements or changes can be made.

What do Metrics Show

• First, metrics help to define what data needs to be monitored. By setting KPIs and metrics, businesses can identify which data points are most important and focus their resources on gathering and analyzing that data. Without metrics, businesses may find themselves gathering and analyzing data that is not useful or relevant.
• Second, metrics provide an indication of progress. By tracking certain metrics, businesses can assess their progress toward their goals and objectives. This allows them to adjust their strategies and better focus their resources.
• Third, metrics can help identify areas of improvement. By tracking key metrics, businesses can identify areas that need improvement, such as customer service times or lead generation. This can result in more efficient and cost-effective operations.

Metrics are useful for many applications, including software development, customer service and operational performance.

For software development, metrics can be used to monitor the progress of a project, how quickly tasks are being completed and how defects are being addressed. Metrics can also be used to compare a project’s performance to that of similar projects or to identify areas where additional effort is needed.

Сategories of Metrics

Metrics can be divided into two main categories: quantitative and qualitative.

Quantitative metrics measure the performance of a data system in terms of numbers or data points. Examples of quantitative metrics include throughput, latency and error rates.

Qualitative metrics measure the performance of a data system in terms of user experience or customer satisfaction. Examples of qualitative metrics include customer feedback, user engagement and ease of use.

There are a variety of metrics that can be used to measure performance, depending on the data and the goals of the organization. Some of the most common metrics include:

1. Speed: How quickly data is processed, stored and read from a system. Speed is typically measured in either megabytes per second (MBps) or megabits per second (Mbps).

2. Availability: A measure of how often a system is available and how quickly it can respond to requests. This metric is usually expressed as a percentage.

3. Response time: The amount of time it takes for a system to respond to a user’s request. Response time is usually measure in milliseconds.

4. Latency: The delay between when a request is made and when it is fulfilled by the system. Latency is typically measured in milliseconds.

5. Throughput: Measures the amount of work that can be performed by the system within a specific period of time. Throughput is typically measured in number of transactions per second (TPS).

6. Accuracy: Measures the accuracy of information received from the system. Accuracy is typically measured in the percentage of occurrence of a problem.

7. Reliability: Measures the probability of the system being available for use when needed. Reliability is typically measured in uptime percentage of time that a system is available for use.

Acure 2.2

The Collection of Metrics in the New Release

Of course, all of the above could not be ignored by Acure. Therefore, a notable update in version 2.2 is a basic implementation for collecting and storing metrics in the system.

Сollecting metrics is carried out through the Data Stream.
The created data stream allows you to simultaneously receive event information (logs), as well as metric data.

For example, for Prometheus to send metrics to the Data Stream, you will need an API key copied from the settings of the corresponding Data Stream.

Based on this, a full-fledged service for analyzing time series and creating rules for managing thresholds is coming soon. UI for managing metrics in the system to create a signal and link it to CI will be implemented in the next release.

The Statistics of the Data Stream (Including Metrics)

In the new release, Data Streams got a Statistics tab, where users can access information about the events (logs) and metrics collected in the data stream.

Information is presented in the form of histograms with statistical indicators.

The Histogram of Events and Logs displays the amount of data received through the Data Stream for the selected period of time with the following indicators:

• Amount of data for the selected period
• Average amount of data for the selected period = amount of data for the period / number of timeslots of the period
• The maximum amount of data for the selected period = the maximum amount of one of the time intervals of the period
• The minimum amount of data for the selected period = the minimum amount of one of the time intervals of the period

The Histogram of Metrics displays the number of Metrics collected from the Data Stream for the selected period of time with the following indicators:

• Quantity for the selected period
• Average quantity for the selected period = number for the period / number of timeslots of the period
• The maximum quantity for the selected period = the maximum amount of one of the time intervals of the period
• The minimum quantity for the selected period = the minimum quantity of one of the time intervals of the period

What Else is in the Release

A new version of the Acure Agent with a built-in HTTP plugin was released. This allows requests to the API of external information systems on the Acure system Agent.

In the same release, a new functionality for managing CI types through the system interface has been implemented, which is a significant development of the CMDB service.

Last but not least, Acure added the functionality of providing access to Signals to other Workgroups, which already have access to Signal-related CIs.

Find more information about Acure update 2.2 in the Changelog and try it by yourself in Userspace.

Discuss updates or ask any questions in our friendly community on Discord or on our Community page.

Сообщение Monitoring of Metrics and Other Features of Acure 2.2 появились сначала на Acure AIOps Platform.

The use of data observability is becoming increasingly important as organizations strive to gain analytical insights from their data. By proactively looking at the data they have available, companies are able to identify trends and issues that could be critical in making decisions and shaping strategies. With accurate and timely observations based on collected data, organizations can quickly detect problems before they become bigger issues, minimizing risk and potential costs.

Additionally, organizations can also use observability techniques to observe how existing systems perform and make necessary adjustments, ensuring that processes are always running smoothly and efficiently. Data observability tools give an organization the ability to make quick adjustments to provide better services for customers or develop more products and services for new markets. Ultimately, investing in a good data observability toolset pays off by allowing organizations to optimize their performance in the long run.

In one of our previous articles, we compared the concepts of observability and monitoring. Although they have some differences, they also share some similarities – for example, the instruments of realization.

How to Choose the Right Observability Tool

Choosing the right observability tools can be an overwhelming task You need to assess different factors such as cost, ease of use, security and compliance issues, data retention length and customizations.

Does the tool provide a generous free plan and pricing based on usage? Is it easy to set up and learn? What integrations are available with existing tools? You should also consider if the tool provides scalability in order to handle larger datasets. Lastly, you will want to think about how much data you want to retain and for how long. Assessing each of these features is key when selecting an observational platform for data.

We hope this article will help you with your choice, because in it we have collected the best full-stack observability tools that you should pay attention to in the new year, based on their main advantages and features.

Best Observability Tools

Datadog

Splunk Observability

Acure.io

Dynatrace

New Relic

Grafana Cloud

Elastic Observability

Lightstep

AppDynamics by Cisco

Chronosphere

Datadog

Datadog is an application performance monitoring solution that helps organizations monitor and troubleshoot their systems. It collects data from applications, servers and other infrastructure components to provide real-time insight into the health of the system. Datadog also provides tools for creating alerting rules, custom dashboards and automated reports. With these features, customers can quickly identify issues before they become problems and take corrective action in a timely manner. Additionally, Datadog allows customers to customize their setup with plug-ins or scripts written in Python or Golang. This makes it easy to extend the platform’s functionality to capture data not already supported by Datadog out of the box.

Overall, Datadog is a comprehensive monitoring and troubleshooting solution for organizations of all sizes. Its breadth of features makes it an excellent choice for both small businesses and large enterprises. Datadog’s ability to collect data from multiple sources, its robust alerting capabilities and its ability to be extended with custom scripts make it a great choice for those looking to maximize performance while minimizing operational costs.

 Most liked features:

• Unlimited integrations
• Frequent releases and stability
• Dashboards available from the get-go

Splunk Observability

Splunk Observability provides an end-to-end observability platform that helps you quickly identify, investigate and troubleshoot issues with your applications. With powerful data search and analysis capabilities, it enables teams to gain real-time insights and visibility into the performance of their systems. The platform comes with various tools for building custom dashboards, visualizations, alerting mechanisms and more for proactive monitoring of system health and performance. It also features built-in ML models to help identify potential areas of improvement or detect anomalies in your data.

Splunk Observability’s intuitive user interface makes it easy to navigate through the platform so you can focus on quickly diagnosing any issues. Additionally, its robust security model helps ensure that all your data is protected and private, reducing the risk of unauthorized access.

Furthermore, Splunk’s global support network helps ensure that technical issues are resolved in a timely manner. All in all, Splunk Observability is the perfect tool for any team looking to gain real-time insights into their application performance.

Most liked features:

• Works well with high volumes of data
• Built-in dashboards
• Customized reports

Acure.io

Acure.io is a self-hosted topology-based AIOps platform for observability and automated remediation. It is a fully SaaS solution with a flexible and open architecture that includes quick and easy tools to find the root cause by topology, time and context with business impact and to aggregate and process any data from any system in a single place. Acure allows you to build and manage CMDB with the low-code engine, visualize the state of the entire IT, run automation from one system for all purposes and quickly and cost-effectively put any application on performance monitoring.

Acure aggregates, normalizes and enriches events collected from various monitoring tools You can connect and extract data from various sources including other popular monitoring systems using ready-made configuration templates and plugins or your own tasks.

Acure uses low-code scenarios to correlate alerts into actionable insights – Signals.  IT operation teams can detect incidents before they become failures.

Acure provides rapid identification of the root cause of an incident. This includes mapping the impact of various technical resources on business services, identifying service and infrastructure changes that cause incidents and highlighting possible bottlenecks.

The dependency map is built automatically based on data from your existing monitoring systems and other tools. This is vital for dynamic environments, such as modern cloud ecosystems and microservices on Kubernetes.

Acure optimizes incident response through the automation of grouping incidents into Signals, two-way ticketing, notifications and chat creation.  Running built-in scripted automation tools with low-code and external runbooks allows workflows to be automated for faster incident response.

Most liked features:

• Ready-made templates for different integrations
• Single dependency map of the whole IT infrastructure, event correlation and noise reduction
• Automation engine
• Rich functionality of the free version

Dynatrace

Dynatrace is a comprehensive, full-stack monitoring platform that enables DevOps and IT operations teams to rapidly detect and triage performance issues. It offers services such as application performance management (APM), infrastructure performance monitoring, log analytics, AI-powered automation and more. The platform helps organizations reduce costs, improve customer experience, streamline processes and stay ahead of the competition.

The platform uses artificial intelligence (AI) and machine learning (ML) to automatically detect issues in your environment before they become major problems. Dynatrace also provides an automated root cause analysis engine which quickly points out the source of these problems so you can minimize downtime and get back on track faster.

Its strong observability capabilities come from its distributed tracing technology that helps you monitor your applications across multiple environments and technologies. Having this visibility, Dynatrace can quickly detect issues in complex architectures to keep your infrastructure running smoothly.

Dynatrace also offers advanced analytics tools that provide insights into customer journeys, application performance optimization opportunities and more. This data can be used to make informed decisions about how to optimize the user’s experience and improve overall efficiency. Furthermore, Dynatrace uses AI-assisted automation to streamline manual processes such as incident management; this optimizes resolution time so you can spend less time troubleshooting and more time innovating.

Most liked features:

• Synthetic monitoring
• AI engine
• Real-time alerts

New Relic

New Relic is a SaaS platform that provides users with the tools and insights to monitor their applications, websites, and digital operations. The platform offers customers real-time data analytics, alerting and monitoring capabilities to ensure the optimal performance of their systems. Additionally, New Relic provides deep visibility into customer architectures to identify root cause issues quickly and accurately.

This allows organizations of all sizes to gain valuable insights into application health as well as user experience metrics such as response time, errors per minute, throughput rates, and more. This can be used to provide feedback on how well an organization’s products perform or detect potential problems before they become a problem for customers.

Moreover, New Relic simplifies the process of managing and monitoring large distributed applications across different cloud environments. It also provides an integrated platform for operations teams to quickly identify, fix and prevent incidents within their environments. This gives organizations the visibility and control they need to improve service availability, thereby boosting customer satisfaction. Additionally, New Relic integrates with other popular business applications such as Terraform, Ansible, and Kubernetes to provide a comprehensive toolkit for automation and analytics.

Most liked features:

• Based on OpenTelemetry standards
• Over 470 available integrations
• AI for incident detection and alerting

Grafana Cloud

Grafana Cloud is a platform for monitoring cloud-based applications and ensuring optimal performance. It includes a query editor, dashboard builder and alert system to ensure the right information is available at the right time.

Grafana Cloud also offers advanced alerting capabilities that monitor metrics and send alerts when something is out of the ordinary. Users can set up alerts for specific conditions such as anomalies, thresholds or other issues that might occur in their environment. Teams can quickly set up dashboards and alerts from their data sources to get insight into their systems. This includes monitoring common metrics such as system health, log analysis for troubleshooting and performance optimization. With Grafana Cloud’s query editor, users can access a wide range of queries to help them easily visualize their data.

Additionally, Grafana Cloud includes integration with popular services such as PagerDuty, Slack and VictorOps to ensure teams are notified quickly when an issue occurs.

The platform also enables secure collaboration between teams by allowing them to easily share insights with colleagues.

Most liked features:

• Free-tier with easy setup
• Fast building and delivering new features
• Informative dashboards
• Perfect for time-series graphs

Elastic Observability

Elastic Observability is an open-source platform for monitoring and managing application performance, resource utilization, security threats and other system metrics. It enables organizations to observe their entire application or environment and provides visibility into the health of their systems. The platform collects data from multiple sources such as application logs, metrics, traces, audit logs and other services to give users a holistic view of their infrastructure. By providing insight into system performance in real-time, Elastic Observability allows users to quickly identify problems before they become costly outages.

The platform includes a range of features that make it easy to monitor your environment and application performance. Its intuitive user interface makes the process of setting up and configuring Elastic Observability simple. Additionally, the platform uses distributed tracing and anomaly detection to help users identify issues quickly. It also offers detailed analytics, alerting capabilities, custom dashboards, and reporting tools to provide visibility into application performance.

Most liked features:

• Quick search
• The possibility to link logs and traces
• APM and log correlation

Lightstep

Lightstep is a monitoring and observability platform designed to help software teams discover, diagnose and resolve issues in real-time. With its powerful distributed tracing capabilities, Lightstep can trace transactions across multiple services, provide insights into system performance and user experience, and quickly detect anomalies that may indicate potential problems. This helps software teams stay informed of the health and performance of their applications as they continuously release new products or features. The platform also provides a unified view of system-level metrics alongside custom application data, allowing developers to easily troubleshoot errors and identify performance bottlenecks.

Lightstep’s modern architecture is built for scalability and resilience, with multi-tenancy support for large-scale deployments. Its open-source agent and cloud SDKs are lightweight and easy to use, enabling customers to quickly implement distributed tracing across their infrastructure. Lightstep is also compatible with popular third-party services such as Kubernetes, New Relic Insights, and Splunk. This allows customers to combine data from multiple sources into a single unified view for deeper insights into their operations.

Most liked features:

• Simple and intuitive interface
• High standard of service support, clear documentation
• Contribution to OpenTelemetry

AppDynamics by Cisco

AppDynamics by Cisco provides an agent-based platform for monitoring and optimizing business applications. It helps identify performance issues, diagnose root causes of outages, and ensure that application code is running smoothly. AppDynamics’ features include real-time analytics, automatic diagnostics, and flexibility to customize the deployment across cloud environments.

With this solution, organizations can track every transaction from end-to-end across distributed systems using automatic tracing technology called “Business Transactions”. This feature enables quick identification of potential problems while providing insights into user experience based on snapshot views of data at any given time. In addition, AppDynamics also offers a range of products such as Server Visibility Tools to help monitor application infrastructure, and Business iQ which provides business-level application performance metrics.

Using AppDynamics’ agentless architecture, detailed data can be collected from applications running in public clouds as well as private on-premise systems. This enables a unified monitoring approach that can identify anomalies and detect problems across different application components. The platform also includes advanced analytics such as anomaly detection to quickly pinpoint issues, code-level diagnostics for identifying root cause of the issue, and machine learning algorithms for automating issue resolution. These capabilities make it easier for businesses to proactively manage their application performance and availability.

Finally, AppDynamics by Cisco comes with integrated security features such as user authentication and authorization so organizations can protect their IT environment while also keeping their performance data secure.

Most liked features:

• Integrating business and technology metrics
• Consolidated observability, anomaly detection and root cause analysis
• Alerts with useful custom actions

Chronosphere

Chronosphere is a powerful tool for managing large-scale distributed systems. It provides an intuitive visual interface that simplifies the deployment, operation, and monitoring of multi-node systems. By leveraging the power of cloud computing and container orchestration technologies, Chronosphere enables organizations to quickly deploy highly available infrastructure with minimal effort.

Chronosphere is designed to provide scalability and fault tolerance across multiple nodes and data centers. For example, it can be used to efficiently scale up or down resources based on service demand while maintaining high availability in production environments. The platform also includes sophisticated alerting features to ensure rapid response when problems arise. This helps reduce downtime and ensures that services remain responsive despite heavy workloads or unexpected outages.

In addition to its scalability and fault tolerance features, Chronosphere also provides a range of other powerful tools for managing distributed systems. These include cost optimization tools to reduce operational costs, as well as monitoring tools for tracking system performance. The platform’s analytics capabilities make it easy to identify areas of improvement and uncover potential issues before they become major problems.

Most liked features:

• PromQL function suggestions
• Solving the Prometheus scaling problem
• Customer support and onboarding process

***

Observability is a key pillar of modern data management and selecting the right tools to ensure the highest levels of performance is an important decision. With the rise of cloud-native technologies, the number of observability tools available has grown exponentially.

Utilizing the correct observability tools can have a tangible impact on key business metrics and make downtimes easier to manage. Many of these observability tools offer free or low-cost plans that bring tremendous value with minimal effort. Therefore, it is worthwhile to look closer at the observability stack when deciding which options would be best for each organization. Determining the proper observability tools can be dependent on various factors like technology used and scope of issues, as well as practical matters such as budget and size. We believe this article then provides information to assess needs accurately and select suitable observability tools that could benefit any company.

Сообщение Top 10 Observability Tools to Pay Attention to in 2023 появились сначала на Acure AIOps Platform.

Let’s look at how to do this in Acure using regular expressions and a new local function.

Event name conversion examples

Imagine that you receive a problematic event from the primary monitoring system with the name SomeHost: High CPU utilization (over 90% for 5m).

For this event, we can apply the following regular expression “High.CPU.util.*over.(\\d+)%.*” and open the Signal in a readable form, with the name “CPU > 90%”.

There can be a lot of examples of such transformations, for example, here is another one for a data storage system:

• Initial event name: “C:: Disk space is critically low (used > 90%)”
• Regular expression: “(.*): Disk space.*used.>.(.*)%.*”
• Resulting pattern: “$1 Storage Partition Usage > $2%”
• Signal Name: “C: Storage Partition Usage > 90%”

We have implemented this request in the automation script as a local function that instantly converts values according to the dictionary defined in the same function. Unlike hard-coded global functions, local functions are a playground where you can implement any of your ideas within a C# script.

How event name conversion works in Acure

To repeat such conversions in Acure, you need to create a local function in the Automation script and transform the Signal name before opening the signal.

Function parameters:

Incoming pin – Input – a string containing the name of the event.

Outgoing pin – Result – a string containing the converted value.

Function code:

***

If the function finds a regular expression in its dictionary that matches the original event name, this value will be converted according to the pattern specified in the dictionary. If there is no matching regular expression in the dictionary, the original value will be returned.

Read more about the functionality of the automation engine in the corresponding section of the Documentation.

Do not forget to share your cool ideas in our Community or Discord channel, and we will add them to our functionality in turn.

Сообщение Acure Life Hacks: Local Function for Event Name Conversion появились сначала на Acure AIOps Platform.