As everything good in life, serverless also comes with its downsides. One of them is the infamous “cold start”. In this article, we’ll cover what they are, what influences serverless startup latency, and how to mitigate its impacts in our applications.

A common scenario for log analytics is that many log events are high value for real time analytics, but there are also events that are low value for analytics, but account for a very large percentage of overall log volume. Often these same low value logs are used only for ad-hoc investigations from time to time or need to be retained for audit purposes.

Serverless lets you deploy applications far away in a data center of a cloud provider. This relieves you of the lion’s share of operational burdens. The more you buy into your cloud provider’s ecosystem, the less you have to do yourself: no more OS updates or database bugfix installations. But you still need to do some operation-related work on your own. For instance, monitoring your application to know what’s going on in that far away data center.

CloudOps is on the up. This is in part due to the rapid acceleration of the shift to cloud that was caused by the pandemic. The shift allowed companies to innovate faster, enjoy greater flexibility and scalability, and become more cost efficient. Many organizations who rapidly adopted cloud or increased their usage now realize that they need to better manage their cloud investments in order to fully embrace these benefits.

Early this year, we set out on a journey to onboard a new cloud engineering team at JFrog. Many can relate to the challenges involved with onboarding a new team, these were amplified even more during the pandemic. However this blog post is not about COVID-19, it is about sharing our experience of fine-tuning the onboarding path for this unbeatable group. TL/DR: What it takes to build and onboard a team of junior engineers into the existing JFrog Cloud engineering team.

Splunk Cloud Architect Paul Davies recently authored and released the GCP Application Template, a blueprint of visualizations, reports, and searches focused on Google Cloud use cases. Many of the reports included in his application require Google Cloud asset inventory data to be periodically generated and sent into Splunk. But HOW exactly do you craft that inventory generation pipeline so you can "light-up" Paul's application dashboards and reports?

Planning a hybrid application migration? There’s plenty to deal with already, and now your manager wants to know—how are you going to make sure that the migration is a success? The secret is to take a subjective judgment and turn it into an objective one. As you probably know, there is no way that you can guarantee a problem-free migration. Don’t leave it up solely to how your boss or anyone else feels about the migration.

Running and troubleshooting production services requires deep visibility into your applications and infrastructure. While basic logs and metrics are available out of the box with Google Cloud Compute Engine (GCE), capturing advanced data used to require the installation of both a metrics agent and a logging agent.

A cloud platform can be described as a storage place that is highly accessible, flexible, scalable and agile in all its characteristics. Users from anywhere via the internet can access their data, collaborate, share, and work together in real-time with the cloud, which means anything less than a cloud platform cannot be possible to comprehend today. The substantial dominance of cloud platforms is their authenticity and usability.