Operations | Monitoring | ITSM | DevOps | Cloud

Several weeks ago, my good friend Katie Nickels (Director of Intelligence at Red Canary extraordinaire) and I were chatting about Ransomware. She was super interested and passionate about some new uses of a ransomware variant named “Ryuk” (first detected in 2018 and named after a manga/anime character) [1]. I was, to be honest, much less interested. It turns out, as usual, Katie was right; this was a big deal (although as you will see, I’m right too… still dull stuff!).

With the promise of unprecedented potential, artificial intelligence (AI) and predictive analytics have permeated into every field of business. Due to their ability to help retail staff serve customers better, personalize video recommendations based on users’ preferences, reduce employee churn, and detect fraud and security threats, AI and predictive analysis are rapidly being adapted across industry verticals.

Sleuth is a deployment tracking tool that gives you a deeper level of insight into your CI/CD workflows by tracking all of your team’s deployment tools from a single dashboard. Sleuth integrates with different components of your deployment pipeline and develops an understanding of your development processes. It can then automatically alert you as to when code is shipping, when manual approvals are needed, and when failures occur.

Amazon SQS is a message queuing service that allows you to send and receive huge numbers of messages from a queue using a simple API. Using Amazon SQS, without setting up any infrastructure, you can have a distributed and fault tolerant queuing system. Since SQS is a managed service, you have less visibility with traditional monitoring tools. As such, it becomes even more important to take advantage of the available monitoring tools in AWS.

Across the technology and IT infrastructure domain, log files are recognized as often time-stamped files that can virtually record all critical information about events occurring within the purview of your IT network, OS, or other software applications. Some log files are humanly interpretable, while others are largely meant for machines to consume.

All databases provide a place to run applications. Monitoring an infrastructure is usually based on its technical components which goes on to extrapolate the health of its applications and programs. However, wouldn’t it be more efficient to monitor the application’s functionality itself? So imagine you have an Order application that consists of a Web UI frontend, Web API backend, business service and an Oracle Database.

Monitoring information that matters to you will often come from disparate sources – whether you are a server engineer, a SQL database administrator, or an application owner wanting a 360 view of your applications’ health. For example, you may want to visualise your server metrics from SCOM alongside historical trends from the SCOM Data Warehouse.

Over the past four days, Grafana Labs' ObservabilityCON 2020 brought together the Grafana community for talks dedicated to observability. We hope you enjoyed all of the sessions, which are available on demand now. (Link to them from the schedule on the event page). The conference wrapped up with predictions and advice from observability experts, lessons in failure, and Grafana Labs team members showcasing ways Grafana and other tools fit into an observability workflow.

Managing large-scale deployments efficiently and resolving issues in a timely manner can be an easy task. What you need is a reliable and agile set of infrastructure monitoring tools for your enterprise IT infrastructure that possesses all the needed features for simple and stress-free management.

Docker recently announced that, starting November 1 2020, pull rate limits will apply to anonymous image pulls from Docker Hub. For anonymous (unauthenticated) users, pull rates are limited based on the individual IP address, and therefore some service disruption was expected for Docker Hub users. Bitbucket is working with Docker to ensure that Bitbucket Pipelines users can continue transparently using Docker Hub without rate limits nor any configuration.