Why I miss my crowbar..

The beauty of having a real crowbar in an office is the social aspect. What is your crowbar?

For the last ~12 years of my career I had a crowbar in my desk drawer. It wasn’t a very long crowbar as you picture in your head, but it had the proper look and feel of a very strong piece of steel to it. I had a very special attachment to it. It made me feel like I am doing real – actual – work and that helped me fall asleep at nights. I actually used it once for work purposes to unbox a server that was shipped from Tokyo to our local datacenter – it was boxed ‘real good’ by a shipping company. Not sure if the shipping costs were higher than the price of a new server! To clarify, I am a Cloud Consultant and my tools are normally far from a crowbar.

It was unintentional

I remember I brought the crowbar to the office by accident one day as I was doing something at a friends place and had the tool with me in my bag and then just left it to the office the next day without a thought.

I brought the crowbar to the office by accident one day as I was doing something at a friends place and had the tool with me

The social aspect

The real beauty of having a real, physical, crowbar with you in an office is the social aspect. In a large office, people quickly start to refer to you as ‘the guy with the crowbar’; or they ask you to show it to new employees as they are doing their first introduction rounds etc. It is an awesome ice-breaker! Imagine the water cooler chats when you walk around with it and people start asking you why you have it with you. Sometimes I even took it with me to meetings to (jokingly) set the expectations (performance review meetings, hello)!

Nowadays as companies no longer run their servers in the basement or pollute the planet with heavy server shipments I need to find the feeling of ‘real work’ from elsewhere. Recently, it has become apparent that my role at Solita Oy as a Senior Cloud Consultant is exposing me to such depth and bredth of real life customer projects that I sleep very well even without my crowbar in the office! The cloud is simply full of benefits for everybody, every size and maturity.

What is your crowbar?

Do you have a similar, unique, item that you have memories of? If you don’t, think if there is something in your life that you could utilise.

While I have since left the crowbar at home from my workplace, at Solita Oy, I find myself contemplating about bringing it back.

Let’s see if the crowbar makes a return during 2019 to the water cooler!

No public cloud? Then kiss AI goodbye

What’s the crucial enabling factor that’s often missing from the debate about the myriad uses of AI? The fact that there is no AI without a proper backend for data (cloud data warehouses/data lakes) or without pre-built components. Examples of this are Cloud Machine Learning (ML) in Google Cloud Platform (GCP) and Sagemaker in Amazon Web Services (AWS). In this cloud blog I will explain why public cloud offers the optimum solution for machine learning (ML) and AI environments.

Why is public cloud essential to AI/ML projects?

  • AWS, Microsoft Azure and GCP offer plenty of pre-built machine learning components. This helps projects to build AI/ML solutions without requiring a deep understanding of ML theory, knowledge of AI or PhD level data scientists.
  • Public cloud is built for workloads which need peaking CPU/IO performance. This lets you pay for an unlimited amount of computing power on a per-minute basis instead of investing millions into your own data centres.
  • Rapid innovation/prototyping is possible using public cloud – you can test and deploy early and scale up in the production if needed.

Public cloud: the superpower of AI

Across many types of projects, AI capabilities are being democratised. Public cloud vendors deliver products, like Sagemaker or CloudML, that allow you to build AI capabilities for your products without a deep theoretical understanding. This means that soon a shortage of AI/ML scientists won’t be your biggest challenge.  Projects can use existing AI tools to build world-class solutions such as customer support, fraud detection, and business intelligence.

My recommendation is that you should head towards data enablement. First invest in data pipelines, data quality, integrations, and cloud-based data warehouses/data lakes. So rather than using over-skilled AI/ML scientists, build up the essential twin pillars – cloud ops and skilled team of data engineers.

Enablement – not enforcement

In my experience, many organisations have been struggling to transition to public cloud due to data confidentiality and classification issues. Business units have been driving the adoption of modern AI-based technology. IT organisations have been pushing back due to security concerns.  After plenty of heated debate we have been able to find a way forward. The benefits of using public cloud components in advanced data processing have been so huge that IT has to find ways to enable the use of public cloud.

The solution for this challenge has proven to be proper data classification and the use of private on-premises facilities to support operations in public cloud. Data location should be defined based on the data classification. Solita has been building secure but flexible automated cloud governance controls. These enable business requests but keep the control in your hands, as well as meeting the requirements usually defined by a company’s chief information security officer (CISO). Modern cloud governance is built on automation and enablement – rather than enforcing policies.


  • The pathway to effective AI adoption usually begins by kickstarting or boosting the public cloud journey and competence within the company.
  • Our recommendation – the public cloud journey should start with proper analyses and planning.
  • Solita is able to help with data confidentiality issues: classification, hybrid/private cloud usage and transformation.
  • Build cloud governance based on enablement and automation rather than enforcement.

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AWS Summit Berlin 2019

My thoughts on the Berlin AWS Summit 2019

What is an AWS Summit?

AWS Summits are small, free events that happen in various cities around the world. They are a “satellite” event of the re:Invent which takes place in Las Vegas every year in November. If you cannot attend re:Invent, you should definately try to attend an AWS Summit.

Berlin AWS Summit

I have had the pleasure of attending the Berlin AWS Summit for 4 years in a row.

Werner Vogels

The event was a 2 day event held on 26-27 of February 2019 in Berlin. The first day was more focused for management or new cloud users and the second day had more deep-dive technical sessions. The event started with a keynote held by Werner Vogels, CTO of Amazon. This year the Berlin AWS Summit seemed to be very focused on topics around Machine Learning and AI. Also I think this year there were more people attending compared to 2018 or 2017.

You will always find other sessions that are interesting to you, even if ML&AI are currently not on your radar. For example I attended the session about “Observability for Modern Applications” that showed how to use AWS X-Ray and App Mesh to monitor and control large scale microservices running in AWS EKS or similar. App Mesh is currently in public preview and it looks very interesting!

The partners

Every year there are a lot of stands by various partners showcasing their products to the passers by. You can also participate in raffles with the cost of your email address (and obvious marketing emails that will ensue). Most of them will also hand out free swag, stickers or pens etc.

stands 1Stands 2Stands 3

Solita Oy is an AWS Partner, please check our qualifications on the AWS Partners page.

Differences to previous years

This year there was no AWS Certified lounge which was a surprise to me. It is a restricted area for people who have an active AWS Certification where they can network with other certified people. I hope it will return next year again.


Thank you for the event!

Thank you and goodbye

Modern cloud operation: successful cloud transformation, part 2

How to ensure a successful cloud transformation? In the first part of this two-part blog series, I explained why and how cloud transformation often fails despite high expectations. In this second part, I will explain how to succeed in cloud transformation, i.e. how to move services to the cloud in the right way.

Below, there are three important tips that will help you reach a good outcome.

1. Start by defining a cloud strategy and a cloud governance model

We often discuss with our customers how to manage, monitor and operate the cloud and what things should be considered when working with third party developers. Many customers are also interested to know what kinds of guidelines and operating models should be determined in order to keep everything under control.

You don’t need a big team to brainstorm and create loads of new processes to define a cloud strategy and update governance models.

To succeed in updating your cloud strategy and governance model, you have to take a very close look at things and realise that you are moving things to a new environment that functions differently from traditional data centers.

So it’s important to understand that for example software projects can be developed in a completely new way in the cloud with multiple suppliers. However, it must be kept in mind that this sort of operation requires a governance model and instructions on what kind of minimum requirements the new services that are to be linked to the company’s systems should have and how their maintenance and continuity should be taken care of. For instance, you have to decide how you can ensure that cloud accounts, data security and access management are taken care of.

2. Insist on having modern cloud operation – choose a suitable partner or get the needed knowhow yourself

Successful cloud transformation requires right kind of expertise. However, traditional service providers rarely have the required skills. New kinds of cloud operators have emerged to solve this issue. Their mission is to help customers manage cloud transformation. How can you identify such operators and what should you demand from them?

The following list is formed on the basis of views presented by Gartner, Forrester and AWS on modern operators. When you are looking for a partner…

  • demand a strong DevOps culture. It forms a good foundation for automation and development of services.
  • ensure cloud-native expertise on platforms and applications.It creates certainty that an expert who knows the whole package and understands how applications and platforms work together is in charge of the project.
  • check that your partner has skills in multiple platforms. AWS, Azure and Google are all good alternatives.
  • ask if your partner masters automatic operation and predictive analytics. These skills reduce variable costs and contribute to quick recovery from incidents.
  • demand agile operating methods, as well as transparency and continuous development of services. With clear and efficient service processes, cost management and reporting are easier and the customer understands the benefits of development.

Solita’s answer to this is a modern cloud operation partnership. In other words, we help our customers create operating models and cloud strategies. A modern cloud operator has an understanding of the whole package that has to be managed and helps to formulate proper operating models and guidelines for cloud development. It’s not our purpose to limit development speed or opportunities, but we want to pay attention to things that ensure continuity and easy maintenance. After all, the development phase is only a fraction of the whole application life cycle.

The developer’s needs are taken into account, and at the same time, for instance the following operating models are determined: How are cloud accounts created and who creates them? How are costs monitored? What kind of user rights are given and to whom? What sort of development tools are used or what targets should be achieved with them? We are responsible for deciding what things are monitored and how.

In addition, the right kind of partner knows what things should be moved to the cloud in the first place.

When moving to cloud, the word move doesn’t fit very well in this context because it is rarely recommended just to move workloads. That is why it’s better to talk about transformation, which means transforming an existing worksload at least with some modifications towards cloud native.

In my opinion, application development is one important skill a modern cloud operator should master. Today, the cloud can be seen as a platform where different kinds of systems and applications are coded. It takes more than just the ability to manage servers to succeed in this game. Therefore, DevOps culture determines how application development and operation work together. You have to understand how environments are automated and monitored.

In addition to monitoring whether applications are running, experts are able to control other things too. They can analyse how an application is working and whether it is performing effectively. A strong symbiosis between developers and operators helps to continuously develop and improve skills that are needed to improve service quality. At best, this kind of operator can promise their customers that services are available and running all the time, and if they are not, they will be fixed at a fixed monthly charge. The model aims to minimise manual operation and work that is separately invoiced per hour. For instance, the model has allowed us reduce our customers’ billable hours by up to 75%.

With the addition of knowledge on the benefits and best features of different cloud services, as well as capacity use and invoicing, you get a package that serves customers’ needs optimally.

3. Don’t try to save in migration! Make the implementation project gradual


Lift & shift type transfers, i.e. moving old environments as they are, don’t generate savings very often. I’m not saying that it couldn’t happen, but the best benefits are achieved by looking at operating models and the environment as a whole. This requires a comprehensive study of the things that should work in the cloud and how the application is integrated in other systems.

The whole environment and its dependencies should be analysed, and all services should be checked one by one. After that you plan migration, and it is time to think what things can be automated. This requires time and money.

A migration that leads to an environment that has been automated as much as possible is a good target. It should also lower recurrent costs related to operation and improve the quality of the service.

Solita offers all services that are needed in cloud transformation. If you are interested in the subject, read more about our services on our website. If you have any questions, please feel free to contact us!

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Deploying an application on a global scale

Running your application on global scale is now much more easier than ever before, here i go through one scenario how to achieve this.

Building and deploying an application on a global scale is now easier than ever. Using the cloud you can easily have your application running close to the customers no matter where they are located.

There are some things to take into consideration when planning and building a deployment. In this post I am using Microsoft Azure service offering as an example but at least Amazon Web Services and Google Cloud Platform have similar services available.

As with real estate, most important thing is location, location, location.

Your end user location defines which cloud to use and where to push applications. China is a totally different game compared to running everything in EU/US area.

Make sure that your application is built to scale from the start, for example DB should be something that is geo-replicated. SQL or Cosmos DB on Azure.

Once you have mapped the regions where an application will be mostly used you can start planning the deployment process.

Traffic manager for geo-balancer

Use the Azure traffic manager to route incoming requests into the nearest region to get the lowest latency from application to end users. Also, with this design if one region is having an outage, the nearest one will continue to serve the customers. Also make sure you put different regions into separate resource groups as this lets you manage each region as a single collection.

Failover can be done with a Traffic manager health probe, which probes the application and checks the health of app services, storage and DB. Make sure you follow design patterns on the health probe so that some lower priority outages don’t mark the whole regions as unavailable.

Traffic manager also supports several routing methods, and, in this case, we would be using Geographic as we want to use location as deciding factor where to route traffic.

Multiregion deployment needs some extra attention

For storage, the best option is to use Read-access geo-redundant storage (RA-GRS) as this gives best replication options for this use case. But there are some caveats to consider when using this option. For example, if there is a zone wide outage then there is a short time period when the data is in a read-only model until the failover happens from region to region.

Deploying an application into a single region is pretty straightforward. But as we are planning to do a multi-region deployment, we should deploy the application into multiple regions in an automated fashion. If you are using Azure DevOps, all you have to do is make several deployment slots to push the application into different regions.

This article covered just one scenario about what to consider when deploying an application to the cloud. When you build your application to be cloud capable from day one, the more benefits the cloud can offer. Don’t let the old ways hold you back. Explore and test different workloads, try containers and see how easy it is to have a true scaling and build deployment pipelines in the cloud.

Choosing provider for cloud

Sticking with your old habits and misconceptions is dangerous, choosing cloud partner is something that should be done with care.

There is nowadays a plethora of cloud operators to choose from and almost everyone has their favourite. AWS is the oldest and probably has the most features and services, Azure is go to place when running Microsoft-related applications or workloads and if you are looking into using AI or ML you go with Google. This has been a common misconception.

In reality choosing your cloud is not so black and white. Providers who came into the game a bit later than Amazon have been investing heavily on the development and are fast catching up. Amazon haven’t been resting on AI or ML front either. And there is also Alibaba, the Amazon of China, who is also pushing hard on the west now and seems to have focus on AI and ML.

Relying on this kind of categorising is dangerous as cloud operator strengths could change quite quickly and it might limit your capability to operate efficiently.

This is where you need to focus. Map your main goals when using the cloud. Check the options available by yourself if your skillset is up to date with all the options. This might be almost impossible as cloud providers are pushing new services almost daily. So I highly recommend that you move to the most important step and choose a partner to help you.

Choosing your partner right can make some serious cost saving and accelerate your development. Do your homework and spend some time benchmarking potential partners. Make sure your partner has enough real life experience on running and building to cloud.

Modern cloud operation: successful cloud transformation, part 1

Today, many people are wondering how they could implement cloud transformation successfully. In the first part of this two-part blog series, I explain why and how cloud transformation often fails despite high expectations. In the second part, I will describe how cloud transformation is made and what the correct way of migrating services to the cloud is.

Some time ago at Solita HUB event, I talked about modern cloud operation and successful cloud transformation. Experiences that our customers had told us about, served as the starting point for my presentation. I wanted to share some of those also with you.

People have often started to use the cloud with high expectations, but those expectations have not really been met. Or they have ended up in a situation where nobody has a good picture of what things have been moved to the cloud or what has been built there. So they’ve ended up in cloud service mess.

People have often started to use the cloud with high expectations, but those expectations have not really been met.

In recent years, people have talked a lot about the cloud and how to start using it. Should they move their systems there by Lift & Shift their existing resources as they are, or should they make new cloud-native applications and systems? Or should they do both?

They might have decided to make the cloud transformation with the help of their own IT department, using an existing service provider or – a bit secretly – with a software development partner. No matter what the choice is, it feels like people are out to make quick profits and they haven’t stopped to think about the big picture and how to govern all of this.

The cloud is not a data centre

Quite often I hear people say “the cloud is only somebody else’s data center”. That is exactly what it is if you don’t know how to use it properly. When we think how the systems of a traditional service provider or our own IT departments has been built, it’s no wonder that you hear statements like this.

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Before, the aim was to offer servers from data center with maintenance and monitoring for operating systems. The idea was that first you specified what kind of capacity you want and how environments should be monitored. Then it was agreed how to react to possible alerts.

The architecture has been designed to be as cost-efficient as possible. In this model, efficiency has relied on virtualisation and, for instance, on the decision whether to build HA systems or not. Especially solutions with two data centers have traditionally been expensive.

When people have started to move this old operating model to the cloud, it hasn’t functioned as they had planned and hoped for. Therefore, it can be said that the true benefits of the cloud will not be gained in the traditional way.

Cloud transformation is not only about moving away from own or co-location data centers. It’s about a comprehensive change towards new operating methods.

It is very wise to build the above-mentioned HA systems in a cloud, because they won’t necessarily cost much or are build-in features. The cloud is not a data centre, and it shouldn’t be considered as one.

Of course, it’s possible to achieve savings with traditional workloads, but still, it is more important to understand that operating methods have to change. Old methods are not enough, and traditional service partners don’t often have adequate skills to develop environments using modern means.

Lack of management causes trouble in cloud services

In some cases, services are built in to cloud together with a software development partner. They have promised to create a well-functioning system quickly. And this can be the case in the cloud at its best. But without management or an proper governance model, problems often occur. The number of different kind of cloud service accounts may increase, and nobody in the organisation seems to know how to manage the accounts and where costs come from.

In addition, surprisingly often people believe that cloud services do not require maintenance and that any developer is able to build a sustainable, secure and cost-effective environment. They are surprised to notice that it’s not that simple.

‘No-Ops’, and maybe the word ‘serverless’ could belong to this same category, are terms that unfortunately have been misunderstood a bit. Only a few software development partners have corrected this misunderstanding, or they haven’t realised themselves that cloud services do require maintenance in reality.

It’s true that services that function relatively well without special maintenance can be built in the cloud, but in reality, No-Ops doesn’t exist without seamless cooperation between developers and operations experts, in other words DevOps culture. No-Ops does mean extreme automation which doesn’t happen on its own. It really isn’t possible everytime, and it is not always worth pursuing.

At Solita, operation has been taken to an entirely new level. Our objective is to make us “useless” as far as daily routines are concerned. We call this modern cloud operation. With this approach, we have, for instance, managed to reduce our customers’ hourly billing considerably. We have also managed to spread our operating methods from customers’ data centers all the way to the cloud.

In my next blog, I will focus on things that should be considered in cloud transformation and explain what modern cloud operation means in practice.

Anton works as a cloud business manager at Solita. Producing IT cost-efficiently from desktops to data centers is close to his heart. When he is not working on clouds, he enjoys skiing, running, cycling, playing football. He is excited about all types of gadgets related to sports and likes to measure and track everything.

Impact of AI