2022 Gartner® Magic Quadrant™ SIEM
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As organizations embrace the DevOps approach to application development they face new challenges that can’t be met with legacy monitoring tools. Teams need DevOps Visibility. While continuous integration, automated testing and continuous delivery have greatly improved the quality of software, clean code doesn’t mean software always behaves as expected. A faulty algorithm or failure to account for unforeseen conditions can cause software to behave unpredictably. Within the continuous delivery (CD) pipeline, troubleshooting can be difficult, and in cases like debugging in a production environment it may not even be possible.
DevOps teams are challenged with monitoring, tracking and troubleshooting issues in a context where applications, systems, network, and tools across the toolchain all emit their own logging data. In fact, we are generating an ever-increasing variety, velocity, and volume of data.
The mantra of DevOps is to "Release faster and automate more." But these goals can also become pain points. Frequent release introduces new complexity and automation obscures that complexity. In fact, DevOps teams cite deployment complexity as their #1 challenge.
The current challenges for DevOps teams is:
DevOps drives cross-organizational team collaboration. However, organizations amidst a DevOps adoption are finding they are having difficulty in collaborating across silos. Frequent release cycles also adds pressure when it comes to syncing multiple development work-streams. These forces are driving the need for more integration between existing legacy tools, and the need for new tools that cross-organizational teams can use collaboratively.
Because of its emphasis on automated testing, DevOps has also created a need for toolsets that enable troubleshooting and root-cause analysis. Why? Because, as I've said, clean code doesn’t mean software always behaves as expected. That's why a greatest pain point for many of these teams is additions and modifications to packaged applications - often these are deployed to multi-tenant cloud environments.
DevOps teams are discovering that performance and availability problems have increased with more frequent releases. That means Ops is spending more time troubleshooting, and development is being drawn into production troubleshooting. In response developers typically will ssh into a server or cloud environment, drop down to the command line, and tail -f the log file. When the problem isn't readily seen they begin grepping the logs using regular expressions and hunt for patterns and clues to the problem. But grep doesn't scale. Simply put, log data is everywhere. Application, system and network logs are stored in different locations of each server, and may be distributed across locations in the cloud or other servers. Sifting through terabytes of data can take days.
The difficulty is there's no consistency, no centralization and no visibility—
Sumo Logic provides a single solution that is tool-agnostic and provides visibility throughout the Continuous Integration-Continuous Delivery pipeline, as well as across the entire DevOps toolchain. Sumo Logic delivers a comprehensive strategy for monitoring, tracking and troubleshooting applications at every stage of the build, test, deliver, and deploy release cycle.
The one reaction I hear from customers is surprise - An organization will typically apply Sumo Logic to a specific use case such as security compliance. Then they discover the breadth of the product and apply it to use cases they had never thought of.
“Many benefits and features of Sumo Logic came to us as a surprise. The Sumo Logic Service continues to uncover different critical issues and deliver new insight throughout the development/support lifecycles of each new version we release” -- Nathan Smith, Technical Director, Outsmart Games
Sumo Logic enables DevOps teams to get deep, real-time visibility into their entire toolchain and production environment to help create better software faster. You can check out Sumo Logic right now with a free trial. It's easy to set up and allows you check out the wealth of features including LogReduce, our pattern-matching algorithm that quickly detects anomalies, errors and trending patterns in your data.
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Observability has become one of the most important areas of your application and infrastructure landscape, and the market has an abundance of tools available that seem to do what you need. In reality, however, most products – especially leading open-source based products – were created to solve a single problem extremely well, and have added additional supporting functionality to become a more robust solution; but the non-core functionality is rarely best of breed. Examples of these are Prometheus and Grafana.