In the 2010 decade, we saw a massive migration of infrastructures into the cloud, along with many new technologies and companies being born “cloud-native.” Although there is still a significant percentage of worldwide data stored and applications run on-premises, the 2020 decade will be focused on a new era of making clouds, and applications that run on them, more efficient. This “Cloud 2.0” is already the focus of many teams and companies, as they seek to move away from monolithic architectures in favor of microservices.
It’s important to note, however, that there are several key challenges that DevOps and Engineering teams face when implementing and scaling these distributed, microservice-oriented systems. Achieving observability is crucial for the successful management and efficiency of this “Cloud 2.0,” which many traditional monitoring solutions simply are not built to support. This blog will dive into these points and present how Epsagon addresses these challenges with applied observability for teams that want to make the most of distributed systems.
Microservice-based Distributed Systems
Highly distributed microservice-based architectures make it more difficult to identify and fix problems. They move between serverless and containers that can interact with dozens, or even hundreds, of components with intermingled third-party APIs, all of which significantly increase data volume and complexity.
In these “Cloud 2.0” environments, Epsagon reduces their complexity by enabling full-stack, automated discovery of distributed applications. Out-of-the-box and customizable dashboards, context-rich metrics for containers and serverless, and alerting activated with a click of a button enable you to proactively monitor the health of your distributed applications in production.
APM Tools & Bytecode Instrumentation
Traditional Application Performance Management (APM) solutions rely on bytecode instrumentation that does not scale well, involves significant overhead, and lacks visibility in distributed systems as you move workloads to modern services such as Kubernetes, AWS Lambda, or AWS Fargate.
Epsagon has replaced bytecode instrumentation with a lightweight agent SDK that requires zero code changes. As a result, setting up Epsagon takes less than 5 minutes with both auto-discovery of your stack and auto-instrumentation of your environment to the cloud.
Logging in Distributed Systems
Organizations often turn to their existing unstructured logs to troubleshoot microservices. Logs are inadequate for monitoring and troubleshooting distributed applications, for many reasons:
- There is no correlation between logs of different microservices. It can be 10 times slower to fix issues
- Logs are manually written by Dev/Ops, manually correlated, and often do not contain all the needed data for troubleshooting complex issues
- Logs require ongoing maintenance, reducing the desired developer’s velocity
Epsagon’s granular tracing, with access to all levels of data, tells the story of a transaction or a workflow as it propagates through a distributed system. Epsagon allows users to see every request in a transaction in a highly visual service map and automatically correlates data from logs, metrics, traces, and payloads within the service map view and dashboards to rapidly pinpoint issues. Epsaogn’s ability to correlate obviates the need to manually search through hundreds, even thousands, of logs, as well as the need to tag and index. To ensure you never miss a trace, the platform also enables automated alerting on trace, user, and resource metrics. The unique payload visibility with all the data you need to understand an issue can be mined for operational and business insights.
Lack of tool automation has meant searching logs for what needs fixing, which is highly manual and, therefore, slow. Even open tracing frameworks require extensive training, manual implementation, and maintenance. In contrast, Epsagon offers full automation for increased developer velocity and MTTD/MTTR.
Out-of-the-box automation includes:
- Cloud access
- Epsagon setup
- Integration of metrics, logs, and frameworks
- Zero code changes for instrumentation
- Predefined and custom dashboards
- Automated alerts with pull-down menus for rules
- User customization – with general-purpose components
Insights and Dashboards
Today, Cloud 2.0 is characterized by hyper-growth in data volume, more widespread adoption of hybrid container and serverless environments, and multi-cloud distributed systems comprised of microservices. Now the challenge is how to make sense of all the data collected and use it at an operational and business level. This requires a different kind of monitoring and troubleshooting.
Unique among APM solutions, Epsagon’s applied observability approach to Cloud 2.0 is taking advantage of the mature and very helpful capabilities cloud providers offer in terms of collecting metrics, log data, events, and alerts. Rather than providing redundant capabilities at additional cost, Epsagon’s platform enables customers to make better use of what they’ve already paid for.
For example, in AWS Cloud, rather than having the user buy a logging module, Epsagon collects the logs from AWS Cloudwatch and correlates logs, metrics, and traces to reveal root-cause. In fact, Epsagon’s custom dashboards can replace cloud and other consoles, enabling you to see and correlate data from multiple sources in a single customized view.
Epsagon’s applied observability platform for modern applications enables users to:
- Integrate with cloud providers who are already doing this foundational data collection work
- Automate the integration with the cloud provider
- Make sense (through automated correlation and querying) of the collected metrics, log data, events, and alerts
- Query with menu-driven and customizable configurations
- Receive data and metric-rich understanding of business impacts
Bottom line: Epsagon enables you to be proactive with your observability and focus on what matters most: the business. Try out Epsagon for 14-days and get set up in less than five minutes to see how we simplify distributed systems in the Cloud 2.0 era.