Operations | Monitoring | ITSM | DevOps | Cloud

Trace at Your Own Pace: Three Easy Ways to Get Started with Distributed Tracing

Stepping through a trace is an invaluable debugging workflow, providing a way to follow requests from service to service even as the applications we manage become more complex and distributed. That same complexity can make getting started with distributed tracing feel overwhelming, but it’s important to remember that instrumenting your code is an additive process—you don’t need to boil the ocean. A trace through a thousand services starts with a single ID.

Learn How NS1 Uses Distributed Tracing to Release Code More Quickly and Reliably

Chris Bertinato, Software Architect at NS1, and Nate Daly, Head of Architecture at NS1 along with Jessica Kerr, Honeycomb Developer Advocate, and Account Executive Scott Phillips discuss how NS1 used distributed tracing to scale their organization and accelerate their migration from a monolith to microservices.

Discover Unknown Service Interaction Patterns With Istio & Honeycomb

Istio service meshes enable organizations to secure, connect, and monitor microservices to modernize their enterprise apps more swiftly and securely. With the addition of distributed tracing and powerful observability tooling, platform operators can gain immediate actionable insights about their applications.

Intercom: Building a More Resilient Ecosystem Through Observability

Learn how Intercom implemented Honeycomb’s distributed traces to learn about production. Kesha Mykhailov, Product Engineer at Intercom joins Honeycomb Developer Advocate Jessica Kerr, and Account Executive Michael Wilde to discuss how Intercom uses distributed traces to streamline their observability workflows, allowing their product engineers to learn about and from their production to increase Intercom’s resilience. Topics include.

What is Gremlin?

Today’s technology leaders are facing a reliability gap. Customers expect their apps to be fast and available. But with Devops and distributed systems driving more speed and complexity, it’s harder than ever to find and fix the reliability risks that can impact customer experience–before it’s too late. To close the Reliability gap, we need a reliability strategy. One that’s proactive, measurable, built-in and automated. We need a reliability management platform.

Datadog on Data Engineering Pipelines: Apache Spark at Scale

Datadog is an observability and security platform that ingests and processes tens of trillions of data points per day, coming from more than 22,000 customers. Processing that amount of data in a reasonable time stretches the limits of well known data engines like Apache Spark. In addition to scale, Datadog infrastructure is multi-cloud on Kubernetes and the data engineering platform is used by different engineering teams, so having a good set of abstractions to make running Spark jobs easier is critical.

Asset Management: Hospitality Industry

Asset infinity’s software eliminates spreadsheet utilization. This system is configured to define all locations, categories and equipment & fixed asset register for all the assets in the hotel premises. It helps in monitoring and tracking every asset. With this hotel asset management software you can do depreciation calculations as well.