Operations | Monitoring | ITSM | DevOps | Cloud

Latest Posts

Remote Working: Encrypt 15k Devices in 3 Days? No problem.

Right now, millions of people are working remotely for the first time, and they’re doing so on company laptops and mobile devices. And with millions of these devices now offsite, this throws but one more wrinkle in tech support’s security plans—in addition to worrying about insecure networks and malware attacks, IT must also safeguard against physical theft. Yes, device encryption is the logical fail-safe for such a scenario and a must-have for any remote IT setup.

What is an Ubuntu LTS release?

Come April 23rd 2020, Ubuntu 20.04 LTS will be available. It will be the first LTS version of Ubuntu since the 18.04 release, and in this blog, I want to answer the common question, what is an LTS? For a deeper look at the benefits of using an Ubuntu LTS, there’s a whitepaper for that, for anything else, this post will answer your questions.

Handling the emerging security challenges and possible concept change

With current global crisis spreading into multiple areas of information technologies, it is crucial to learn how are the security-related areas affected, and what it would mean for the entire IT industry. Remote access to network resources results in both increased load on new and existing tools allowing performing most activity remotely (to grasp the possible scale of impact: read, for example, about recent Zoom service controversies).

Five worthy reads: Implementing a successful remote work environment

Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we delve into how organizations are increasingly adopting a remote work model, and how they can equip themselves to build a synchronized virtual workspace. In the wake of COVID-19 and the subsequent mandates to stay at home, many organizations have implemented a remote work environment in order to maintain business operations.

Understanding and Baselining Network Behaviour using Machine Learning - Part I

Managing a network more effectively has been something our customers have been asking us about for many years, but it has become an increasingly important topic as working from home becomes the new normal across the globe. In this blog series, I thought I’d present a few analytical techniques that we have seen our customers deploy on their network data to: Better understand their network and Develop baselines for network behaviour and detect anomalies.

Understanding and Baselining Network Behaviour using Machine Learning - Part II

A difficult question we come across with many customers is ‘what does normal look like for my network?’. There are many reasons why monitoring for changes in network behaviour is important, with some great examples in this article - such as flagging potential security risks or predicting potential outages.

Colonel Mustard in the Library with Microservices APM

As many of us are rediscovering an interest in board games, it feels relevant to make reference to Hasbro’s classic Clue. Understanding what’s going right or wrong in your sprawling digital business can feel a lot like a murder mystery: it was the authentication service in the east region with the memory exhaustion error. This analogy has a weakness when applied to modern operations. The Clue board game had 6 weapons, 6 suspects, and 9 rooms. That’s 324 combinations.

Sharing Code Dependencies with AWS Lambda Layers

The use of Serverless execution models is expanding extremely rapidly and cloud providers are continuing to enhance their platforms. Per Flexera’s “State of the Cloud” report: Leading this trend for the last two years, Amazon has released a few features that address AWS Lambdas’ pain points and make them a more feasible choice for large scale deployments consisting of numerous applications.

Visualizing observability with Kibana: Event rates and rate of change in TSVB

When working with observability data, a good portion of it comes in as time series data — things like CPU or memory utilization, network transfer, even application trace data. And the Elastic Stack offers powerful tools within Kibana for time series analysis, including TSVB (formerly Time Series Visual Builder). In this blog post, I’m going to attempt to demystify rates in TSVB by walking through three different types: positive rates, rate of change, and event rates.