I’ve always been fascinated by ideas. The kind of ideas that spark innovation, creativity, and problem-solving. The kind of ideas that make you want to jump out of bed and start working on them right away. That’s why I was drawn to the famous tagline from Idea Cellular company: “An idea can change your life” And it did.
Ideas are powerful. They can transform industries, create new solutions, and shape the future. But how do you cultivate a culture of innovation in your organization? How do you foster an environment where ideas are welcomed, nurtured, and implemented?
That’s where an idea engine comes in. An idea engine is a system that helps you generate, evaluate, and execute ideas effectively. It’s not just about brainstorming sessions or suggestion boxes. It’s about having a clear process that allows you to tap into the collective intelligence of your team and turn ideas into reality.
We frequently ask questions to gather requirements and provide our designs and solutions. Many organizations standardize their questions for consistency among teams. Can chatbots handle these questions? Yes, AI services can be utilized to make decisions and trigger DevOps pipelines to deploy the desired design or service.
By using Infrastructure as Code (IAC), we can quickly deploy design templates using AI to assist in choosing the appropriate design. This allows customers to focus on workload migration instead of landing zone design. Although, not every customer is the same, for example, a secure Azure VNet hub and spoke design can be deployed initially and improved upon while testing non-critical workloads in the cloud. We can drive move from design workshop to design selection workshop where you are helping the customers to pick up one of best design available.
Another solution is deploying services on an existing subscription, where customers can quickly deploy VMs or PaaS services by answering a few questions posed by a chatbot, without waiting for a human response. This speeds up the deployment process and increases customer satisfaction.
In conclusion, by utilizing AI and chatbots, customers can avoid creating tickets and waiting for support, as they can immediately provision resources by answering questions and confirming with AI suggestions.
Last week, Microsoft announced the Preview of Capacity Reservation for VMs. You can reserve VM capacity in your DR region to ensure that you have VM resources available to create or turn on your protected VMs using ASR. ASR does not guarantee that your VMs can be turned on in your DR region in the event of disaster recovery. So, capacity reservation is a welcome feature and much needed. However, this is increasing the cost of your solution again.
ASR protected VM cost
Capacity Reservation Cost ( as same as your actual VM cost)
Note: DR is not just the VMs but including other components. I did not provide the details above because it applies to both the options.
Hmm.. Can we plan a DR cost-effectively in Azure? Let’s take a look:
The long waiting feature is now Public Preview. When there is a Azure region disaster recovery, we need our VMs to be turned on in the secondary region. This feature guarantees you the recovery. You may learn about this feature in this URL.
As you know already, Azure Site Recovery does not 100% guarantee to turn on your VMs in the event of DR. This feature addition helps you gaining more confidence with your BCP with this feature addition.
Take a look at the Microsoft statement about the use cases for this feature.
Business-critical applications—use on-demand capacity reservations to protect your capacity, for example when taking these VMs offline to perform updates.
Disaster recovery—you now have the option to set aside compute capacity to ensure a seamless recovery in the event of a natural disaster. The compute capacity can be repurposed to run other workloads whenever DR is not in effect. The VM maintenance can be handled by keeping core images up to date without the need to deploy or maintain VMs outside of DR testing.
Special events—claiming capacity ahead of time provides assurance that your business can handle the extra demand.
I have been asking for this feature for a long time now, and finally, it is here. I am happy about Microsoft as they are listening to customers and partners. However, the first bullet point is a bit worrisome as it states, It is not guaranteed to get your VM back if it is offline for some time due to maintenance. Does MSFT force customers to take this for all the critical workload? I hope they do not make things worse to this point.
What are the standards we should follow when we move on to Public Cloud?
We often get this questions during the Public Cloud conversations with different stakeholders. I would say ‘Change’ should be standard. Ahh…What?
Be ready to accept a Change
Be ready to execute a Change.
Be ready to prepare for future Changes.
The change should start from the minds of people. That means develop a mindset to accept a change is the first thing in the transformation journey. It is the first barrier as we know that each of us are comfortable to continue with existing system because change will bring interruptions, nobody like interruptions.
We hear lot about the automation now a days. Should we automate anything and everything? Yes, most of it. However, we must understand why do we need to bring automation. As far as I understand, we need to automate if it relates to below mentioned points at least.
Is it a repeated task?
Does it save time during deployment (like saving down time)
Does it avoid human error?
Does it bring standardization in repeated tasks?
I have seen engineers trying to codify everything which might waste hours of time or days, but it could have done in few minutes vs hours vs days. I have done such things in the past, but it is for learning though.
I remember I learned about a frog that lived in the well. Since frog was in the well entire his life he thought that the Well is the world and there is nothing beautiful than that until the water in the well dried and frog had to come out of it.
We should not be that FROG in the well.
There are lot of things in the world that we have not learned and seen yet. We must be open to learn. You might be able perform well in your job today. But we need to think about tomorrow. The world is changing too fast, so we need to learn faster and act swiftly to survive in the world.
It is not just about learning, we also need to look around and check are we doing it properly. It this the best of doing? There are 100s of people in the world doing similar stuff differently. It is a challenge to get know about how others are doing. That is where you need to collaborate with others, engage yourself with others in the world, hear other, share your thoughts, arranged hackathons to bring new ideas and encourage openness in the team to bring new thoughts. We never know, the ideas can come from junior in the team. Remember an idea can change your world !!!
Yes, most of us work in Technology companies those advise many organizations globally for taking technological decision and encourage them to use the latest and advanced technologies to automate their operations. However, how many of those companies are using technology within their organizations and drive innovations for their internal requirements. Both the employees and employers are suffering because a proper system is not in place for solving the problems like Lack of effective appraisal system, identifying the right resources for the projects, unable to stop the talent leaving the organization etc. Let’s look at those and how we can try to solve using the technologies like Machine Learning(ML) and Artificial Intelligence(AI). Yes, we are in the world of Machine Learning(ML) and Artificial Intelligence (AI) and we must now start thinking about using them effectively.
Machine learning is ‘predictive analysis’ in very simple terms, agree? Arrive into a conclusion by analyzing the data. Can this possible only with computers? We, human beings do it on a daily to basis, to catch a bus, to drive a car, to shop and what not.
Don’t be confused. Let me try to explain and don’t blame me at the end if that doesn’t work, a pre-bail has been taken :-).
Let me take the example of how we learn driving. Excuse me for those who never tried it 🙂.
The driving instructor gives you first set of data like usage of steering wheel, gear shifting, clutch, brake, accelerator etc. Initially, with those basic data you mess with clutch, gear, accelerator and brake often. Then you slowly correct the mistakes by practicing which means you are learning by feeding your brain with additional data on how to use it effectively. Eventually you get it correct when you have more and more data; and create your own algorithm to drive your car. Result of this you start applying the break softer, start shifting the gear smoothly. That is exactly the machine learning does with the help of your intelligence (it is currently being replaced with Artificial Intelligence –AI 🙂). Continue reading “Machine Learning: I do it, you do it everyday without a computer”