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Performance Optimization of Tax Management Services on Kubernetes


An organization providing tax management and planning solutions turned to Altoros to optimize the performance of its Kubernetes clusters and evaluate their security.

Performance Optimization of Tax Management Services on Kubernetes

About the project

Brief results of the assessment:

  • With a six-hour working session and subsequent report delivered within a week, Altoros evaluated the customer’s platform against 25 maturity model components and provided an assessment of the current state and a roadmap for prioritized improvements.
  • The performance bottleneck was identified and a remediation plan defined.
  • As recommended, by employing a defense in-depth strategy—including image registry scanning, CIS benchmark testing, and governance with policy management—the organization has a clear path forward for security improvements.
  • The customer will realize better standardization, streamlined operations, and ability to scale using Altoros’s recommendations for automation via CI/CD pipelines.
  • Observability will be enhanced by employing Altoros-provided monitoring recommendations.

The customer

Headquartered in San Francisco, the company is a provider of international tax management and planning services. The organization assists enterprises in global tax law tracking, comprehensive tax analysis, as well as entity charts management and tax planning. The company serves end users from over 100 countries.

The need

The customer hosted its tax management and planning services on the Kubernetes platform. The system was already employed by 7,000+ users daily, so the company wanted to ensure its services would be stable and available under higher loads. Furthermore, the customer was seeking an independent, third-party security review of the solution.

Relying on Altoros expertise as a certified Kubernetes service provider, the company wanted to optimize performance, enable scalability, andensure enterprise-grade security of its services.

The challenges

The company is a growing international tax management and planning provider with heavy workloads that need to scale elastically. Due to the sensitivity of working with tax, being able to optimize, secure, and regularly update the services is crucially important to the business.

The solution

In this project, Altoros applied a maturity model that has been field-tested during six years of experience in creating cloud-native solutions with Kubernetes and other platforms.

Favoring a holistic approach, our DevOps experts interviewed the customer’s engineering team over the course of two technical sessions to evaluate the maturity of the existing platform and identify potential issues. Within a week, a report was provided that contained recommendations ranked by priority and based on impact and complexity for each of the model’s 25 core components.

By assessing app / container deployment mechanisms in use, the team at Altoros identified opportunities for improving load distribution, which should increase performance and eliminate potential single points of failure.

To enhance cluster security, our engineers advised a defense in depth strategy, including image registry scanning, CIS benchmark testing, and governance with policy management.

Our team also provided recommendations for automating operations in continuous integration / delivery pipelines to standardize and automate operations, which should also have a positive impact on security and ability to scale globally across multiple geographic regions.

To enable better decision-making and identify potential problems, such as when to scale or if a component is overloaded, Altoros provided guidance on monitoring using Prometheus and Grafana.

To help avoid downtime during maintenance, our team provided guidance on using a pod disruption budget.

The outcome

Partnering with Altoros, the customer was able to assess the maturity of its Kubernetes-based services, identify bottlenecks, and create a roadmap for prioritized improvements. The customer has a clear path forward and a close partnership with Altoros for implementation and support.

Technology stack


Amazon Elastic Kubernetes Service

Programming languages

JavaScript, C#

Frameworks and tools

.NET Framework, AWS Lambda, Azure Insights, CloudAMQP (RabbitMQ), Jenkins, Prometheus, Grafana, Jaeger, SocketCluster, Istio


Amazon RDS, MongoDB, SQL Server, PostgreSQL


reduced build time


users daily


countries served


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Ryan Meharg

Ryan Meharg

Technical Director

ryan.m@altoros.com650 265-2266

4900 Hopyard Rd. Suite 100 Pleasanton, CA 94588