Operations | Monitoring | ITSM | DevOps | Cloud

Often when completing a migration project, you’re having your organisation straddle between two systems. You’re fighting habits and changing attitudes while also attempting to complete a high-risk operation. Every software team at one stage in their career will have to complete a migration. Whether it’s to improve scalability and performance, or transition between an on-prem to cloud solution, you’ll need a deep understanding of your current environment to create a strategy that minimises downtime for your team.

Monitoring CPU load and memory usage is common practice, but with serverless no action is required. In this video, we quickly explain that if your Cloud Run instances start hitting high CPU load, Google Cloud will automatically spin up new instances for you, and vice versa!

Kubernetes configurations are complex to manage across developers and operators. External tools like Helm, Kustomize cannot ensure environment-specific configurations and admission controllers provide a way to do this. Now, various tools have evolved over time that helps solve this problem - OPA Gatekeeper, Kyverno, Kubewarden and jsPolicy. In this talk during ContainerDays 2021, Saiyam Pathak from Civo goes through the need for a policy engine and discusses how each of the tools help along with the differences between them and where these are headed to.

Product Pricing Isn’t Hocus Pocus. . . Scott Weitzman sits down with Alex Barnes to discuss what exactly Revenue Growth Management is, how it works, and why now is the most important time to focus on consumer retention. As Scott learns, this is not just some magical system that makes prices, but rather something that allows CPG companies to understand their consumers better and help meet them at the shelves.

In April 2021, HashiCorp completed the Consul Global Scale Benchmark where Consul updated 172,000+ services running on 10,000 nodes on AWS in under 1 second. Over the course of the experiment, we logged over 1.8 Billion log events in Datadog.

At Vacasa, AWS accounts represent the unit of isolation for distinct applications & services in our software ecosystem, providing security benefits and operational autonomy for our teams as we scale. Managing accounts at this scale requires strong DevOps practices to maintain security, operational sanity, and uniform observability across the system. In this talk, we’ll cover the benefits of such an approach, the practices that make it possible, and the important role Datadog plays.

When application delivery performance issues happen, observability is critical to diagnosing the problem at hand. The adage “it’s always DNS” means that observability must extend to the foundational layers of the application delivery and access networking stacks. Yet granting administrative access to core network services like DNS and DHCP may run contrary to an organization’s least-privileged access policies. In this session, attendees will learn how global internet companies and enterprises use NS1 and Datadog to provide democratized DNS observability and reach optimal application performance.

Observability is trending. Organizations that rely on cloud infrastructure and cloud applications prioritize observability initiatives to get control over their business’s applications. At the same time, we see the “gap” between the on-premises infrastructure and “non-cloud” infrastructure is becoming bigger. Examples are End User Computing (EUC) and Global networks (SD-WAN).

Using managed services is all very well, but how do you get the data you need from the different services into Datadog so you can see it all in one place? This session will walk through the configuration for bringing your Aiven-managed Apache Kafka service metrics into your Datadog explorer. You’ll see how to filter the metrics to focus on specific topics or consumer groups, and how to use the Aiven client to create a repeatable, scriptable setup. This session is recommended for anyone living in the as-a-Service world who cares about data and is interested in using metrics to optimize their Kafka clusters.