Get your solution cloud-ready, one service at a time and host it wherever you want
Do you have trouble scaling?
Are you growing across continents?
Is your hosting provider expensive?
Do you find it challenging to manage your own infrastructure?
Why do you benefit from migrating into the cloud?
- Reduce management overhead
- Gain access to managed tools like Kubernetes, Azure DevOps, Jenkins, IoT/Event hubs
- Easier automated testing
- Better scaling
- Faster releases
The cloud offers managed and unmanaged services from application down to infrastructure level that can optimize and reduce costs, if applied well. You can use these services on demand temporarily or permanently, tailored to your system's need. A cloud solution should be architected and designed to take advantage of built-in tools for management, monitoring and be able to scale components independently. We strive to enable this for all our projects.
how we work
To utilize different, scalable services (databases, queues, storages, middleware, etc.), software needs to be architected towards this goal. Of course, not all solutions were designed with that in mind, so we help in refactoring and rearchitecting it by applying cloud-patterns and plan a close-to-zero downtime migration. Changing the foundation of any software is a tough mission which affects data as well as code. We support you all the way into the cloud with all the assets and dependencies you need.
- Break up your system into micro-services
- Migrate your release and test pipelines to the cloud
- Move and secure your data storage
- Create monitoring and alerting
Take advantage of changing your solution into a micro-service architecture
Are new components becoming harder to integrate?
Very few people are able to understand your system?
Do your requirements frequently change on components?
Did your technology age so much, a rewrite may be cheaper?
Any change introduces more bugs then it fixes?
You are unable to scale pieces/components independently, or at all?
Why do you benefit from distributed ecosystems?
- Scale any part of the system
- On-demand scaling
- Apply measure-change-measure on a smaller scale
- Utilize the full power of Docker and Kubernetes
- Increase robustness of core dependencies
When a system grows, individual components tend to change at different paces. Monolithic architectures make it harder for A-B-Testing and canary techniques to eventually replace and sunset components inside your ecosystem. This is where a distributed system has its strengths, allowing a specialized look at one component at a time during all development phases. When taking distributed systems, a step further, they are called micro-service architectures which have been increasingly popular over the years.
how we work
After identifying layers and components that are suitable to be stand-alone and separated, they can be decoupled and moved into their own space. This allows you to develop and scale them individually without impacting much of the remaining system. Key components become more resilient and are less affected by other, frequently modified parts. For more information you can check Microsoft's architecture e-book
- Change your architecture to support micro-services
- Identify high risk components in your system
- Decouple and increase cohesion
- Find bottlenecks and tackle them individually
Built-in security from the ground up with Microsoft's SDL approach
Do you have data to protect?
New regulations require you to secure certain components?
Your team is specialized in a different area?
Why do you benefit from added security during development?
- Identify possible attack vectors upfront
- Establish cryptography and encryption requirements
- Data lakes and warehouses require security just as your API endpoints do
Secure access to endpoints reduces likelihood of successful attacks. Adding security in the late stages of development or even after components went live, is not only tricky but also expensive and takes time to do. With SDL, security concerns are moved to the earliest stage they can be addressed at. We have multiple certified specialists that come from a Microsoft background to implement SDL in our projects.
how we work
Different components in a distributed system are vulnerable to different kinds of attacks and must live up specific regulations introduced by governments all across the globe. Techniques from SDL help us to eliminate issues before they make it into the final product. The remaining concerns can be found and tackled repeatedly using code analysis, penetration testing and behaviour analysis during runtime.
- Analyze the application structure during design
- Use penetration testing techniques to receive real data
- Add incident reporting systems
- Use static and dynamic analysis methods to find deficits
- Add single sign-on through Azure AD to all services
Transform your raw, structured or unstructured data into valuable information
Are your data queries slow?
Do you have multiple, unstructured storage dumps, but no ETL in place?
Building data connections is a manual, tedious process for you?
Do additional, added information in your data storages consequently break your dashboards?
Why do you benefit from transforming your data?
- Structured, optimized datasets can be queried efficiently
- Automated pipelines feed your data into systems that use them
- Compressing data saves space and allows historical insights
- Create or adjust workflows that support your processes
Storing all your data seems quite easy at first, but as requirements change, new business processes are added and more data is needed to gain additional insights, the storage strategy changes and should be redesigned accordingly. There is no single way to store data to be perfect for every use case. ETL and ELT have been effectively used for pipelining, connecting, crunching, compressing and serving data to systems and users alike.
how we work
Making use of connectors and ML-supported tools, many solutions provide efficient and flexible access to on-premise and cloud data storage. ETL and ELT processes feed the data with an optimized format into tools that require fast access on specific structures. By transforming and squashing, queries on your data sources can be improved, optimized and enriched to allow new perspectives and insights on your business. We work with DataBricks and Microsoft Azure to enhance your data on a fundamental level, so your workflows improve.
- Access and connect your data sources automatically, efficiently and scalable through Apache Spark or Azure SQL Data Warehouse (Synapse)
- Integration and hosting via DataBricks or Microsoft Azure
- Transform and modify your data to save costs, gain insights and add value with Azure Data Factory and Azure Synapse
business analytics & visualization
Analyze and display your data to the advantage of different user roles
Are you tired of slow dashboards?
Is your data hard to understand?
Does your management work with the same visualizations as your technicians?
Why do you benefit from using advanced business analytics?
- Complex data requires simplified visualization to be processed
- Call to actions should be based on data to back them up
- Consolidated data can lead to better understanding of your users, your systems, your own business
- Data-based assessment of risks and opportunities
Data is quite easy to generate and store. Connecting and displaying it for use as a guide or proof is harder, but usually worth the trouble. Further development on your solution should always be backed by real data (where possible) and their logical connections. The same data can be used to gain insights into your funnel, into data evolution, into customer retention and other valuable fields.
how we work
Different user roles inside a company have different requirements on which they can base their decisions. Identify those requirements to aggregate your datasets into meaningful dashboards and views to support decision-making. We use different frameworks to offer you the ideal representation of your data so you can make the most of it.
- Power BI deals with very large datasets and supports various flexible dashboards
- Custom views can be implemented with dedicated graphical frameworks like D3
- Rulesets add an additional layer of usability on visualizations
Release fast, release often and react to issues and vulnerabilities with routine
Do releases break your live system too often?
You cannot get new features running fast enough?
Is the time lost in deployment needed somewhere else?
Why do you benefit from better deployment structures?
- Continuous integration/delivery are proven to work well
- Releases can be scary, but they do not have to be
- Shift more towards development time by spending less time on unoptimized deployments
Making frequent releases to be a habit will reduce the total time spent on planning and scheduling them. This is achieved by automating everything into an execution trigger. Customers and users benefit from zero-downtime techniques that can be integrated into CI/CD pipelines. Frequent releases can improve customer happiness and increase the bond between product and users.
how we work
Building on existing technologies for CI/CD pipelines, automated testing and monitoring is a reliable, proven foundation for many solutions. Different technologies for identifying faults and security concerns are available for almost any programming language and framework. They run your test suites and provide feedback via hooks and pipes back into CI/CD pipelines and logging/monitoring solutions. Most technologies offer flexibility and customization down to code level, this enables you to seamlessly integrate them into your workflows.
- Use pipelines through Jenkins, Azure DevOps, Github Actions
- Utilize the many benefits of automated testing
- Take control with measuring through your monitoring and logging solutions (ELK, Azure Monitor, etc.)
Detect bugs and errors that lead to security risks before deployment
Do your security issues only show up on live systems?
Are your users the target of attacks?
The lack of information regarding your security status is a concern?
Why do you benefit from increased security measures during deployment?
- Every issue that arises after deployment increases costs and pressure
- Many issues can be found automatically and programmatically
- Increase user confidence by eliminating potential issues
Any bug or issue found by or affecting a user is expensive, increases frustration amongst all affected parties and can become a customer success nightmare. The release process is the last bastion before a change or feature goes live, therefore it is also the last opportunity to identify issues and problems, especially when your data or program security is at stake.
how we work
The CI/CD pipeline is but a mere framework to plug your tools into. Static code analysis, third party security analyzers, self-written test suites and many other options reduce the potential of building, approving, and releasing a bug. These methods need to be established and integrated. Ideally, they grow and adjust with your solution’s needs and challenges.
- Specialized tools in the deployment pipeline analyze the code (SonarQube, etc.)
- Automatic tests include security-related use cases
- Evaluate potential risk of third-party components
- Monitor inter-process communication
alerting & monitoring
Generated data is valuable and brings insights into complex situations and urgent issues
Errors are found and reported by angry users?
Do you want to know about your system status?
Detailed reports are too hard to build and outdate quickly?
There are random data errors across your system?
Why do you benefit from generating alerts and reports?
- React early with alerts on downtimes, accessibility and execution errors
- Detect scaling and load issues when they arise
- Check your system health
- What you cannot measure, you cannot improve
In many solutions multiple modules communicate with another, use data sources and generate a business value. Since very few of these solutions are simple, knowing what exactly happened, happens and (ideally) will happen is information that can give you an edge towards your competitors or prevent churn. Therefore, valuable data needs to be collected and connected in such a way that it allows you to make founded decisions and reactions to situations.
how we work
Business and related data across the whole ecosystem can be collected raw and dumped into stashes (i.e. Logstash). The connection between different raw data is made in alerting (i.e. Graylog) or visualization (i.e. Kibana). This is the kind of data that grows over time and can be aggregated to provide historical insights.
Real-time data is mostly used to determine system health and usage and rarely is retained over time, therefore different technologies are available (i.e. Prometheus & Grafana) to cover ephemeral datasets. In a micro-service world, the different modules communicate with each other all the time, different data snippets travel far. Understanding how and when and where they travel can increase awareness and impact software deployment and implementation structures.
- The ELK/EFK stack can connect any kind of data generated across your ecosystem
- Prometheus & Grafana provide real-time monitoring and alerting options
- Monitor the data flows for increased understanding with Jaeger & Istio