Operations | Monitoring | ITSM | DevOps | Cloud

Deep Learning Toolkit 3.1 - Release for Kubernetes and OpenShift

In sync with the upcoming release of Splunk’s Machine Learning Toolkit 5.2, we have launched a new release of the Deep Learning Toolkit for Splunk (DLTK) along with a brand new “golden” container image. This includes a few new and exciting algorithm examples which I will cover in part 2 of this blog post series.

Deep Learning Toolkit 3.1 - Examples for Prophet, Graphs, GPUs and DASK

In part 1 of this release blog series we introduced the latest version of the Deep Learning Toolkit 3.1 which enables you to connect to Kubernetes and OpenShift. On top of that a brand new “golden image” is available on docker hub to support even more interesting algorithms from the world of machine learning and deep learning! Over the past few months, our customers’ data scientists have asked for various new algorithms and use cases they wanted to tackle with DLTK.

Manufacturing in Crisis Mode: How Data Power Can Help

For those of you with some gray hair working in the manufacturing business, remember when order intake plunged suddenly by more than 40%? Remember when CFO and Controllers ruled the company, driving painful cost-cutting programs to counter double-digit business losses? It was the time of the Economic and Financial Crisis 2007/08, which forced manufacturing organizations to stare in the abyss.

Using Elasticsearch as a Time-Series Database in the Endpoint Agent

At ThousandEyes and the Endpoint Agent, we have a track record of using Elasticsearch as a time-series database for the metrics that we collect from our agents. I will be presenting how we decided to use Elasticsearch as a Time Series Database (TSDB), and how we got buy-in from stakeholders. Stathis spent several years in Athens, Greece, as a Software Engineer before moving to London. Enjoys working with large distributed systems using technologies like Elasticsearch, Kafka, Java, Kotlin. Wants to build his own tech when he grows up.

Top Four Payoffs of Being a Data Innovator in Financial Services

I recently chatted with Adam DeMattia from leading research and analyst firm ESG in a webinar about data use maturity in financial services. According to the research1, 21% of financial services firms identify as data innovators (compared to 11% of global respondents) — those who make smarter use of data as a matter of strategic importance.

Why Are Financial Services Companies Turning to Data and Analytics to Deliver Improvements in Customer Experience?

Splunk’s recent "What Is Your Data Really Worth?" report1 highlighted the importance of data and analytics to financial services companies. In our global survey of business and IT decision makers2, 89% of respondents from financial services companies felt that the intelligent use of data and analytics is becoming the only source of differentiation in the industry.

IT Operations: The Value of Data

I recently participated in a webinar exploring the question "What is Your Data Really Worth?" in the context of financial services. Enterprise Strategy Group (ESG), in partnership with Splunk, performed a global research survey of 1,350 business and IT decision-makers across leading economies and industries. Over the course of the webinar we discussed their findings with my participation focused on IT Operations.

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