OpsCruise Launches Kubernetes-Optimized, Real-Time AWS Serverless Observability
OpsCruise is offering an extension to improve serverless observability with Amazon Web Service. The release is purpose-built for Kubernetes, leverages AI/ML and can also monitor many popular AWS cloud components.
OpsCruise has a new observability extension for Amazon Web Services serverless to provide DevOps teams real-time visibility, control and problem detection. OpsCruise also works with all application components, Kubernetes and the supporting infrastructure.
Specifically, OpsCruise monitors multiple cloud components in the AWS cloud, including Lambda functions, API Gateways, SQS queues, ECS containers, Kinesis streams, and DynamoDB tables. It also adds machine learning and pre-built integrations to the mix to help discover and remediate issues quickly, OpsCruise execs noted.
"Traditional monitoring solutions rely on collecting metrics and custom distributed tracing to track service requests to and from the serverless components. Unfortunately, the burden of detecting and understanding problems is left as a DIY offline exercise for the engineers," said Scott Fulton, Co-Founder and CEO of OpsCruise. "In contrast, OpsCruise enhances the visualization of the dynamic topology and state of applications, and also extends its automated and predictive ML and AI capabilities to serverless components as well."
As part of its serverless observability offering, OpsCruise monitors multiple cloud components in the AWS cloud, such as Lambda functions, API Gateways, SQS queues, ECS containers, Kinesis streams, and DynamoDB tables.
The OpsCruise product page at the AWS Marketplace adds further context to its approach and use cases.
OpsCruise assures the health and performance of enterprise cloud applications using contextual AI and ML, a SaaS delivery model and an embedded open source and cloud monitoring foundation.
When enterprises migrate their applications to the cloud, they can lose visibility and understanding. The architecture is more complex with many sub-components, e.g., APIs, cloud services, outside their control. Further, the business and app teams are rolling out changes more frequently. The net result is performance degradations or resources are over-provisioned. This can delay projects and cause SRE and ITOps teams to lose time and productivity.
OpsCruise's software uses contextual ML to understand cloud applications in real time and predict performance degradations before users notice. Further, it provides a closed-loop model through automated causal analysis and actions, which improves Ops staff productivity.
Quick Look at OpsCruise Key Capabilities
OpsCruise's more notable features and benefits include:
Purpose-built for Kubernetes: The OpsCruise platform is engineered with deep understanding of Kubernetes observability. It is aware and can detect issues with pods, containers, worker nodes, replicasets, deployments, service meshes and more – and offers enterprise-caliber auto-scaling. Then it couples all this deep K8s knowledge with machine learning to empower teams to quickly understand your workloads and the issues that pertain to them.
Combines monitoring and configuration data for contextual visibility: OpsCruise lets users integrate multiple signals (including those from logs, metrics, flows and traces) with important change data from events, configuration and CI/CD platforms. Once combined, this data is viewable in an application graph for powerful context. Users can also automatically understand how app components are related to one another, even with third-party cloud services. OpsCruise also reveals how app components are dependent upon Kubernetes and underlying infrastructure. Users can also track all changes in their stack, no matter whether they are infrastructural, configurations or deployments.
Easy-to-use contextual Kubernetes monitoring: OpsCruise also supports 'zero-touch' configuration and automatic discovery and monitoring of dynamic, ephemeral microservice workloads that run inside containers on Kubernetes and associated cloud services. Without performing context switching, users can bring Kubernetes data together with infrastructure data, application data and logs. The OpsCruise Dynamic Cluster Map provides pre-built visualizations of the health, interdependencies and SLAs within the Kubernetes cluster.
Predicts issues before they cause problems: OpsCruise enables users to detect problems using its 'predictive behavior' modeling. This feature automatically learns an application's behavior and can surface problems across app components, Kubernetes and supporting infrastructure. Users can also visualize performance using flow tracing in real-time without code changes or a service mesh.
'Topology walks' to help eliminate the 'ware room': OpsCruise goes beyond correlations that look only for events that occur around the same time or area. Users can leverage the knowledge of their complete application structure through 'topology walks,' which help pinpoint problem sources far down the dependency chain. This approach also avoids the need to navigate between different screens thanks to OpsCruise's automated causal analysis, which proactively links unexpected behavior changes to breaches.
Up & running quickly: OpsCruise can be deployed in minutes via Helm. Once launched, it automatically collects metadata on pods, deployments, services, and nodes. There is no need to deploy agents on each host, K8s sidecars or change code. It also integrates with popular tools users already use for monitoring and alerting, container orchestration and more.
Democratizes observability thanks to open source: OpsCruise is an open source and cloud monitoring tool with a wide range of telemetry data. The use of an open source approach provides all-sized companies deep control, enables unlimited reuse and avoids paying fees or subscriptions.
OpsCruise is available through the AWS Marketplace as part of your standard AWS billing as well as through a Free Forever plan where customers can start immediately - no credit card or contract commitment necessary.
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