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SignalFx Supports AWS App Mesh

April 11, 2019

SignalFx expanded its relationship with Amazon Web Services (AWS) with support for AWS App Mesh at launch.

Organizations are adopting microservices to boost innovation by accelerating application development cycles. But distributing application logic from single runtime to distributed services creates huge observability challenges. Development teams are faced with major code updates to instrument every microservice while Site Reliability Engineers (SREs) and Operations teams find it difficult to determine the health of the overall application and where to troubleshoot the root cause of performance issues.

A growing number of companies are turning to service mesh technologies such as AWS App Mesh to address the new operational complexities of distributed service-oriented architectures.

By integrating with AWS App Mesh, SignalFx allows customers to fully realize the power of service mesh by providing real-time visibility and streaming intelligence for problem detection and troubleshooting.

There are many benefits to the integrations, including:

SignalFx enables customers to release new code up to eight times faster

SignalFx automatically captures application performance data from AWS App Mesh

SignalFx provides pre-built service monitoring dashboards with accurate performance metrics so service owners can instantly visualize how services are performing and create precise alerts to quickly respond to performance issues - all without developers having to make any code change.

“Application developers and site reliability engineers are challenged by the complexity introduced by the distributed nature of microservices architectures. By supporting AWS App Mesh, SignalFx provides customers with system-wide monitoring and observability, pre-built visualization, and directed troubleshooting – all critical requirements for confidently adopting microservices at scale,” said Arijit Mukherji, CTO of SignalFx. “Our AWS customers see AWS App Mesh as the easiest way to benefit from service mesh technology.”

Powered by a NoSample™ distributed tracing architecture, SignalFx can analyze every single transaction reported by AWS App Mesh – not just a small random sample – and intelligently capture anomalies – even the P 99 outliers. SignalFx Outlier Analyzer™ pinpoints the most challenging issues with a single click, enabling observability teams with prescriptive directions for troubleshooting and reduced MTTR.

“Customers are increasingly adopting microservices architectures to deliver innovation faster and to make applications more resilient. AWS App Mesh makes it easy to adopt service mesh to standardize communications across microservices and monitor performance data,” said Deepak Singh, Director of Compute Services, Amazon Web Services, Inc. “SignalFx’s support for AWS App Mesh provides our customers with a seamless monitoring and observability solution that allows for real-time visibility and closed-loop automation such as dynamic traffic routing.”

“SignalFx provides us with monitoring, troubleshooting, and analytics in one unified, real-time platform. This allows us to see in more granular detail how our applications are performing as well as the ability to identify problems at a remarkable speed – and act on them faster than ever before,” said Mike Hamrah, Chief Architect, Namely. “We are excited that SignalFx is expanding its relationship with AWS to simplify the adoption of service mesh technology.”

"If you are running or plan to run microservices at scale in production environments, then you should evaluate service mesh technologies. This is especially true if you are already encountering challenges in areas such as observability and visibility, identifying service dependencies, and troubleshooting performance issues. From an observability standpoint, a service mesh can offer compelling benefits by providing consistent access to data related to how services behave and interact with each other during runtime.” noted Stephen Elliot, Program Vice President, Management Software and DevOps with IDC

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