The emergence of cloud computing. Arguably the biggest change in technology in decades, cloud computing changed how technology would now develop and how businesses and organizations would operate. Indeed, the enormous popularity of cloud services is due precisely to that: you can get different models depending on your operational needs. To properly utilize these cloud service models, you should understand the differences in their functional capabilities and the ideal use cases for each model.

Spot Ocean has been recognized as the sole leader and outperformer in the GigaOm 2024 Radar for Kubernetes Resource Management in the Maturity and Platform Play quadrant. The report highlights solutions that help organizations more effectively manage the increasing complexity of Kubernetes environments in the cloud. GigaOm evaluated a number of vendors on their ability to analyze and optimize Kubernetes resources.

In the first article of our series, we explored the importance of trace headers and the complexities involved in their propagation. Now, we shift from theory to practice. This second installment will take you through a hands-on baseline scenario and our initial strategy of propagating the OpenTelemetry trace context in AWS Kinesis by using the PartitionKey parameter.

AIOps is a game changer for MSPs. But how do you implement AIOps to ensure you get those game-changing benefits? Chances are, you’re not interested in spending the resources and time required to build it yourself with all of the development, testing, maintenance, etc. that entails. Instead, AIOps as a service provides you with the capabilities to better manage the IT infrastructure and operations of multiple clients.

The evolution of public cloud over the past few years has been remarkable. Digital transformation, remote work, and AI have created breakneck growth. Back in 2018, before anyone uttered the words COVID or ChatGPT, there were already big drivers for public cloud. The global digital transformation market size was valued at $320 billion, and set for 18% annual growth, to reach a projected $695 billion by 2025.

Cloud migration vs modernization – What are the nuances? Cloud migration involves moving applications and data to the cloud often with minimal changes to their architecture. Cloud migration projects usually aim to leverage cloud infrastructure for benefits such as scalability, flexibility and reduced on-prem maintenance.

Amazon Web Services (AWS) offers the convenience of choosing specific virtual machine combinations to meet your compute needs. Unlike traditional data centers, you can also scale your cloud resources automatically to meet fluctuating workload needs. The best part is that you can rightsize your workload requirements to specific instance types (VM types) offered by AWS. By hand, this takes a lot of time and is prone to errors. This is where AWS Compute Optimizer comes into play.

The notion of moving assets out of the cloud may sound like a step backward in an era where digital transformation is driven primarily by migration efforts into the cloud. But it turns out deliberately shifting cyber assets away from the cloud– known as “cloud repatriation”– can be a highly strategic option for CIOs and enterprise IT teams looking to strike the optimal balance of cost, security, performance, and scalability in their IT environments.

Datadog is like a Swiss Army knife for observability. Whether it’s cloud, applications, or infrastructure, Datadog can serve all your monitoring needs under one roof. This is with a level of integration that’s akin to having a universal remote for all your digital operations, from on-premises to cloud environments. The thing is, with great power comes a notable concern – cost.