The Deep Learning Toolkit (DLTK) was launched at .conf19 with the intention of helping customers leverage additional Deep Learning frameworks as part of their machine learning workflows. The app ships with four separate containers: Tensorflow 2.0 - CPU, Tensorflow 2.0 GPU, Pytorch and SpaCy. All of the containers provide a base install of Jupyter Lab & Tensorboard to help customers develop and create neural nets or custom algorithms.

Let’s face it—distributed streaming is an exciting technology that can be leveraged in many ways. Use cases include messaging, log aggregation, distributed tracing, and event sourcing, among others. Distributed streaming can result in significant benefits for companies that choose to use it, but, when not implemented correctly, it can initiate a frustrating technical debt cycle. How do you know if you’re properly implementing Kafka in your environment?

Teams switching from a monolithic application architecture to microservices often face a jarring realization: their time-tested troubleshooting techniques don’t work as effectively. A microservice consists of many independent, distributed, and ephemeral services with varying capabilities for monitoring and logging. Techniques such as stack traces are effective troubleshooting tools in monoliths, but only paint a small portion of the big picture in a microservice-based application.

Starting April 21, 2020, all requests to Elasticsearch Service on Elastic Cloud must use HTTP over TLS (HTTPS) with support for TLS 1.2. We’ve decided to make this change in the best interest of our users so we can ensure the security of data in transit and stay up to date with modern encryption, security protocols, and practices.

It’s 2020, which means it’s time to look back at 2019 and reminisce about the good times – fun with family and friends, good food, travel, and memories to last a lifetime. Who am I kidding? Everyone remembers the bad stuff. The increasing impacts of climate change; relentless fires in the Amazon, California, and Australia; political and social unrest around the globe; and the last season of Game of Thrones. Jon Snow... you still know nothing.

With 2020 now well underway and the end of our financial year just around the corner, it’s a great moment to review some of the successes we have had in the EMEA Partner team over the past year. One particular highlight for us came in December when Orange Business Services, the digital transformation arm of Orange, named Splunk as its Digital & Data Partner of the Year at its annual awards in Paris.

Hey Everyone, We recently did a webinar with Christian Heger, technical head of the DATEV SOC, as well as Sebastian Schmerl, head of cyber defense of Computacenter. They shared their 6-month path of modernizing their security operations with help of Splunk technology and the MITRE ATT&CK framework. As we weren’t able to address all of the questions during the webinar, we discussed these afterwards and share them in this blog post as a Q&A follow-up.

Does one or more of the following personas describe you? If you fit one of those personas, you are in luck because I’m happy to tell you about some new Splunk integrations with Visual Studio Code in this blog.

In Part 1 we’ve described what container monitoring is and why you need it. Because each container typically runs a single process, has its own environment, utilizes virtual networks, or has various methods of managing storage. Traditional monitoring solutions take metrics from each server and the applications they run. These servers and applications running on them are typically very static, with very long uptimes.

Even though containers have been around for ages, it wasn’t until Docker showed up that containers really became widely adopted. Docker has made it easier, faster, and cheaper to deploy containerized applications. However, organizations that adopt container orchestration tools for application deployment face new maintenance challenges.