Observability vs monitoring, what is the difference? Monitoring is the what to observability’s why. Here we dig into the differences.

Monitoring cloud-native systems is hard. You’ve got highly distributed apps spanning tens and hundreds of nodes, services and instances. You’ve got additional layers and dimensions—not just bare metal and OS, but also node, pod, namespace, deployment version, Kubernetes’ control plane and more. To make things more interesting, any typical system these days uses many third-party frameworks, whether open source or cloud services.

Software development firms need to develop and deploy software solutions and changes quickly, safely, and as demanded by the client. DevOps can help! There’s a major subset of DevOps you can’t overlook: observability.

The best way to be sure that you keep a secret is not to know it in the first place. Managing secrets is a notoriously difficult engineering problem. Across our industry, secrets are stored in a bewildering variety of secure (and sometimes notoriously insecure) systems of varying complexity. Engineers are often trying to balance the least worst set of tradeoffs. At Honeycomb, we asked: What if we didn’t need to know your secrets to begin with?

Databases have always been the backbone of applications – both web and enterprise. Now, more than ever before, you need to know not just overall statistics about your database, but you must identify how database performance interacts with the network, operating system, servers, configuration, and even third party dependencies.

Two popular deployment architectures exist in software: the out-of-favor monolithic architecture and the newly popular microservices architecture. Monolithic architectures were quite popular in the past, with almost all companies adopting them. As time went on, the drawbacks of these systems drove companies to rework entire systems to use microservices instead.

Anodot recently took part in the 2021 Data Agility Day, an event dedicated to examining how organizations are extracting value from data. CEO and Co-Founder David Drai was joined by David Ashirov, VP of Data at Freshly, where he has worked to build a data stack that departments across the company could leverage to drive business. Ashirov is a senior executive with two decades of experience in data engineering, business intelligence, and marketing.

In basically every modern software organization, building software is not just a matter of writing code – it’s a matter of testing it to ensure it works properly, a matter of creating artifacts out of it that can be used by the end customers, and a matter of deploying them to a customer-accessible location for these customers to be able to actually use it.