The Road to Automation in IT Operations-Part 1
November 03, 2021

Anirban Chatterjee
BigPanda

Share this

The buzz around automation continues to grow, in every industry, sector and vertical — and for good reason. In IT Ops, the impact can be instant and huge, with improvement measured in the tens or even hundreds of percent as automation enables even a very lean team to operate at an outsized level. Automation can facilitate faster production, the creation of new products and the delivery of more services — and all in a stable, predictable, scalable way. And today, with AI and Machine Learning in the mix (aka AIOps), the possibilities and potential for automation are almost limitless.

So, how do you ensure your journey to automated IT Ops is streamlined and effective, and not just a buzzword?


Here are 4 golden rules to help you do just that:

1. Set good standards

2. Reduce complexity

3. Define and simplify processes

4. Automate wisely

1. Set good standards — powerful and specific

In general, standards can be thought of as specifications and procedures that have been designed to make sure the materials, products, methods, or services people use every day are reliable. Standardization is particularly relevant to IT automation, which is itself a computerized implementation of a standardized process. Put bluntly, computers are dumb and lack creativity. They do only what they're told, so we have to know exactly what we want them to do before they can do it. This is why only standardized processes can be automated successfully.

The key to optimizing automation is to create powerful standards that enable you to get the most out of your systems. These standards define how your systems communicate with each other, transfer information, look at and analyze data, etc.

A good example is the standardization of naming conventions, which, in the enterprise IT world, is always something of a challenge. If there is no standard in place regarding what one system is sending across, then the receiving system will just be guessing what to do with information it is getting. And, if it can't get the information it needs out of the data stream it receives, then a separate, manually-updated lookup table may be required, compromising the efficacy of the automation you wish to set up.


Consider, for example, the host naming standards illustrated in the image above. The more the naming standard is designed with your needs in mind, the easier it is for your systems to analyze the data, and pull out the critical information needed, such as the affected frame, geographical location, application served, etc. If used consistently across the organization, this standard becomes a solid bedrock for the assumptions that tools downstream can make about the data, and for the automation processes you put in place on top — for example, to issue automated alerts, response and remediation actions when a server has an issue.

2. Reduce complexity - keep only what you need

A useful rule of thumb is that you should be able to sketch out or explain what your IT environment does and how it functions in around a minute

Complexity is inherent in the dynamic modern-day IT environments in which businesses operate, but that doesn't mean that we should not try to reduce it wherever possible. A useful rule of thumb is that you should be able to sketch out or explain what your IT environment does and how it functions in around a minute. If you can't, automation may just exacerbate complexity. So, when you contemplate automation, you should see it as an opportunity to take a step back, recognize areas of unnecessary complexity and identify what can be done to reduce it. To do this properly, you need to make sure you talk to the people that are doing the work on the ground to find out about their actual experience.

In the diagram below, we see an example of how complexity can be dealt with by moving to a SaaS environment. Operating many systems on-premise that need to be managed and maintained comes at a huge cost — both financially and in terms of efficiency. By moving to a SaaS environment, rather than having to maintain hardware, the operating system, bug fixes and patches, network bandwidth, firewalls, load balancers and the on-prem application software itself, you just need to take care of one thing only: the configuration of your SaaS apps!


Tool rationalization is another good example. By reducing the number of tools you work with, you reduce the complexity of your operations.

Now, you can focus your automation efforts on taking care of simplified tasks, saving time and reducing overhead in the long term.

Go to: The Road to Automation in IT Operations - Part 2

Anirban Chatterjee is Director of Product Marketing at BigPanda
Share this

The Latest

January 26, 2023

As enterprises work to implement or improve their observability practices, tool sprawl is a very real phenomenon ... Tool sprawl can and does happen all across the organization. In this post, though, we'll focus specifically on how and why observability efforts often result in tool sprawl, some of the possible negative consequences of that sprawl, and we'll offer some advice on how to reduce or even avoid sprawl ...

January 25, 2023

As companies generate more data across their network footprints, they need network observability tools to help find meaning in that data for better decision-making and problem solving. It seems many companies believe that adding more tools leads to better and faster insights ... And yet, observability tools aren't meeting many companies' needs. In fact, adding more tools introduces new challenges ...

January 24, 2023

Driven by the need to create scalable, faster, and more agile systems, businesses are adopting cloud native approaches. But cloud native environments also come with an explosion of data and complexity that makes it harder for businesses to detect and remediate issues before everything comes to a screeching halt. Observability, if done right, can make it easier to mitigate these challenges and remediate incidents before they become major customer-impacting problems ...

January 23, 2023

The spiraling cost of energy is forcing public cloud providers to raise their prices significantly. A recent report by Canalys predicted that public cloud prices will jump by around 20% in the US and more than 30% in Europe in 2023. These steep price increases will test the conventional wisdom that moving to the cloud is a cheap computing alternative ...

January 19, 2023

Despite strong interest over the past decade, the actual investment in DX has been recent. While 100% of enterprises are now engaged with DX in some way, most (77%) have begun their DX journey within the past two years. And most are early stage, with a fourth (24%) at the discussion stage and half (49%) currently transforming. Only 27% say they have finished their DX efforts ...

January 18, 2023

While most thought that distraction and motivation would be the main contributors to low productivity in a work-from-home environment, many organizations discovered that it was gaps in their IT systems that created some of the most significant challenges ...

January 17, 2023
The US aviation sector was struggling to return to normal following a nationwide ground stop imposed by Federal Aviation Administration (FAA) early Wednesday over a computer issue ...
January 13, 2023

APMdigest and leading IT research firm Enterprise Management Associates (EMA) are teaming up on the EMA-APMdigest Podcast, a new podcast focused on the latest technologies impacting IT Operations. In Episode 1, Dan Twing, President and COO of EMA, discusses Observability and Automation with Will Schoeppner, Research Director covering Application Performance Management and Business Intelligence at EMA ...

January 12, 2023

APMdigest is following up our list of 2023 Application Performance Management Predictions with predictions from industry experts about how the cloud will evolve in 2023 ...

January 11, 2023

As demand for digital services increases and distributed systems become more complex, organizations must collect and process a growing amount of observability data (logs, metrics, and traces). Site reliability engineers (SREs), developers, and security engineers use observability data to learn how their applications and environments are performing so they can successfully respond to issues and mitigate risk ...