Misconfigured resources are a big contributor to compromised cloud security. If you have misconfigured Amazon S3 buckets, for example, malicious actors could access your data, then inappropriately or illegally distribute this private information, putting your company’s security at risk. Policies and regular best practices enforcement are key to reducing this security risk.

Big data applications require distributed systems to process, store and analyze the massive amounts of information that companies are collecting. Apache Spark has become a go-to framework for this, powering use cases from AI and machine learning to data analysis, by providing a unified interface for distributing data processing tasks across a cluster of machines. Spark requires other services to manage the cluster, with YARN and Mesos as two well-known cluster management tools.

The year 2020 was a tough one and tested the grit and resilience of the human race. Organizations across the globe had to prioritize the safety of employees, customers, and associates. The rapid response to COVID-19 has enabled millions to work remotely because of advanced cloud computing technologies supplied through public cloud services like Amazon Web Services (AWS) and Microsoft Azure.

Coralogix can be configured to automatically and dynamically archive logs to an S3 bucket. This saves Coralogix customers money, but of course there are times when the data needs to be reindexed. This operation counts the reindexed logs against the daily quota. Many times customers would like to search and focus on the exact logs to be reindexed or even query the logs outside of Coralogix all together.

The hard part about application modernization isn’t determining whether or not it’s a good idea. It almost certainly is. Rather, the hard part is figuring out how to get started: Which applications you should focus on first, and what’s the best approach to modernizing them. Fully refactoring 1,000 applications from monolith into microservices, for example, might seem like the right goal, but it might also take the rest of this century.

Multi-cloud has become a hot-button topic these days, with a lot of cloud experts taking a strong stance against the practice. There are exceptions and legitimate reasons why you might choose a multi-cloud strategy (e.g., you sell to customers who restrict you from hosting their data in AWS). Extenuating circumstances aside, there are far more reasons why multi-cloud isn’t a good idea.

At Illuminate, Genesys Cloud principal architect Kal Patel shared how they use Sumo Logic, how they manage it at scale, and some of the lessons they’ve learned in the last year.

Serverless has been gaining more and more traction over the last few years. The global serverless architecture market was estimated at $3.01 billion in 2017 and is expected to hit $21.99 billion by 2025. The number is reflected in the increasing amount of enterprises starting to look for ways of decoupling their current monolithic architectures and migrating their stack to serverless. Read more about the popular enterprise use cases for AWS Lambda.

A cloud-first strategy can feel like a big jump from traditional setups. One of the benefits of a hybrid or on-premises strategy is you feel like you’re in control. You and your team know where your critical servers live. You can touch them. Your team understands your security processes, and you can easily verify security personnel follow them. Those are all significant benefits. However, a growing number of software teams are choosing to move to cloud-first strategies.

Even before new hybrid workforce models, many companies already moved a lot of services to the cloud. COVID-19 digital transformation strategies instantly increased the number of access points and endpoints. This led to a rapid increase in event log data followed by all kinds of other issues -- performance, availability, security, and ultimately increased IT costs amongst other things. A centralized log management solution for your cloud environment can help you manage the above and more.