Microservices monitoring with IBM Instana Observability automates application discovery, monitoring, tracing and root cause analysis
Complete and automated microservices observability
IBM® Instana® delivers a monitoring solution with complete observability into your entire microservices environment. Everything is automated, including application discovery, agent deployment and monitoring configuration across your full microservice architecture technology stack. Instana also reduces troubleshooting efforts by eliminating noise and pinpointing the triggering event and likely cause of each incident.
Precise, real-time monitoring of the complete microservices stack means no important microservices metric or trace is missed. Always- Accurate management information is passed to Devops teams increasing response time, for incident prevention and/or triage.
Instana’s Dynamic Graph records and models relationships between all entities (including microservices) in real-time, giving users knowledge of all interdependencies and the ability to break down what’s running or not running at any point in time.
Instana provides a monitoring framework with valuable insights into system performance, enabling development teams to identify runtime failures, areas for improvement and optimize system performance for microservices.
With minimal configuration and out-of-the-box dashboards, Instana is easy to deploy and use, reducing ramp-up time and the skill level needed to get value fast helping monitor microservices quickly.
Bolster monitoring systems strategies with Instana
Microservices allow businesses to shift away from traditional monolithic application monitoring, solving many problems associated with software delivery and application performance monitoring (APM). Running microservices on cloud-native architectures based on open-source tools like Kubernetes or containers, like Docker, also introduce a new level of complexity to application ecosystems environments. When it comes to effectively monitoring functionality and managing service quality across several programming languages, traditional monitoring systems strategies simply fall short in a microservices world.
Features
- Automatic discovery and mapping
- AI-powered root cause analysis
- Contextual traceability
- Real-time performance monitoring
- Automatic anomaly detection
Automatic discovery and mapping of microservices
Microservice monitoring tools can automatically discover and map all the microservices in your environment, including their dependencies and interactions. This understanding can help with the orchestration of workflows.
AI-powered root cause analysis
Analyze all the data collected across distributed systems, identify the root cause of any issues in real-time, and resolve complications before they impact user experience.
Contextual traceability
Get a detailed visualization view of the interactions between different services, including the data flowing between them. Minimize latency and support the quick identification and troubleshooting of performance issues as they arise. Gather time-series data to spot outliers and track patterns over time.
Real-time performance monitoring capabilities
Gain real-time visibility into the service performance of each individual microservice, as well as the overall application lifecycle. Aggregate service level data from containers and applications, monitor APIs and identify the slowest endpoints of your service.
Automatic anomaly detection
Detect anomalies in your microservice environment with end-to-end monitoring, and quickly identify and resolve issues before they impact the end-user.
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Having the ability to measure how well our microservices communicate and understanding the performance of the connections between all components in our platform became vitally important. ”
300+ supported technologies
Instana integrates with other monitoring tools, such as log management and network monitoring tools like IBM® Turbonomic®, to provide a comprehensive view of application performance across the entire IT infrastructure with no plug-ins or application restarts.