Observe, Inc. announced the industry’s first and only Observability Cloud delivering up to a 3X reduction in Mean-Time-To-Resolution (MTTR) of incidents and a 10x reduction in the total cost of ownership.
“At a time when customer experience has never been more important, organizations are struggling with stagnant MTTR times and spiraling tool costs,” said Jeremy Burton, CEO of Observe, Inc., “Observe’s unique, data-centric, approach promises to both simplify troubleshooting and change the economics of Observability forever.”
The Observability Cloud uniquely ingests all event data into an AWS S3-based Data Lake. Next, the event data is curated into a Data Graph, a graph of connected Datasets representing things that users want to ask questions about such as customers, shopping carts, pods, or containers. Finally, Observe simplifies using the Data Graph through a host of pre-built Data Apps for common environments including AWS, Kubernetes, GitHub, and more. Data Apps contain many features familiar to users such as dashboards, alerts, and search, but because they are based on the Data Graph, users can quickly and easily access relevant context during an investigation.
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The Observability Cloud is based on a modern architecture consisting of inexpensive cloud storage and elastic compute. Event data is compressed by an average of 10x and stored for 13 months for no additional charge above AWS S3 costs. Compute is charged based on usage (to the nearest millisecond) when, for example, a user searches, an alert is sent, or new event data is accelerated. The Observability Cloud architecture changes the economics of Observability, which frees users from having to sample, filter, or eliminate event data to manage costs.
Today Observe released several new features to The Observability Cloud supporting a broader range of use cases, simplifying usage, and enabling users to better manage their observability costs.
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- New distributed tracing visualizations and workflows enable both engineering break-fix operations and SRE service-level management. Open Telemetry instrumentation of applications enables users to view top-level dashboards summarizing typical Service Level Objective (SLO or Rate, Error & Duration (RED) metrics. Users can then drill down on any of those metrics, retaining context as they do so, into underlying trace/span or log event data. This is only possible because Observe’s distributed tracing is built on the Data Graph.
- New and enhanced Data Apps for AWS, GCP, Azure, Jenkins, and GitHub make it easier than ever for users to get started with Observe. Data Apps provide the user with everything they need to start observing their environment including dashboards, alerts, searches, Datasets, and more.
- New ‘Smart Dashboards’ enable users to quickly navigate to related context as they triage or investigate issues. Smart Dashboards are built on the Data Graph and allow the user to perform high-level filtering and then drill into areas of interest, while retaining context, even down to low-level event data.
- Enhanced Metrics Expression Builder makes working with metrics in Smart Dashboards and Worksheets easier than ever, eliminating the need to learn OPAL for most common tasks.
- New Credit Management features enable more granular tracking of user activities in usage dashboards, assistance for users constructing complex or expensive queries, and the ability for admins to set hard limits on credit consumption.
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