Consulting and Advisory

Our most experienced engineers enable VPEs and CTOs to overcome major new tech challenges. We do this with a hands-on approach that delivers instant results.

< What We Do

With leading-edge technology consulting and advisory services, we help clients stay ahead of changes like the cloud-native revolution, the evolution of PaaS, FaaS and edge computing, and the rise of AI and machine learning.

Lohika has more than 17 years of experience scaling engineering for the most innovative and demanding technology companies on the planet. Our deep experience and insights have been gained by delivering solutions during a host of disruptions, including the commoditization of Big Data, the cloud-native revolution, the evolution of PaaS, FaaS and edge computing, and the rise of AI and machine learning.

Our spearhead consultants collaborate with VPEs and CTOs to:

  • Ensure that the right architecture and technology choices are made at the early stages
  • Troubleshoot and solve urgent engineering issues to immediately find solutions
  • Implement challenging proof-of-concept for next-generation ideas

Our advisory services are highly specialized and focused. Our clients’ engineering teams rely on our experts for actionable advice on building cloud-native applications, best practices for deployment and observability of those apps, migrating from monolithic to microservices architecture, implementing performance and security testing, designing and fine-tuning data processing pipelines, delivering data science discovery and the productization of ML models.

System Audit
  • Investigate the current limits of a system’s availability and scalability
  • Determine viability of maintaining a system for the short and long-term
  • Confirm whether your system provides enough information to identify the root cause of an issue
  • Make sure that metrics in the system are correct and provide good visibility into what is happening behind the scenes
Read case study
Observability and Monitoring
  • Show when and where things may go wrong
  • Make sure system provides enough information to discover the root cause of an issue
  • Confirm system provides alerts when something goes wrong
  • Verify that distributed system tracing and monitoring data is actionable
AI DevOps
  • Use a tailored, sophisticated approach to make AI work in production on different platforms
  • Connect data scientist, infrastructure, machine learning and data engineers
  • Focus on orchestration, integration, optimization
Data Science
  • Question efficiency of the existing decision-making processes and assumptions
  • Extract meaningful data and actionable insights to drive business decisions
  • Improve decision-making process with the help of statistics and ML algorithms
  • Incorporate ML-driven decision making into a current analytical system or a data pipeline
Read case study
Cloud Migration
  • Provide a strategy for the migration of existing on-premise application into a cloud
  • Ensure that application is auto-scalable in order to handle continuous business needs
  • Minimize failure risks and increase reliability via auto-redundancy and geo-redundancy
  • Advise on best practices for efficient auto-provisioning of system resources
Read case study
Automated Deployment Pipeline
  • Decrease feature time to market and ensure resource allocation transparency
  • Consult on best approaches to enable a constant flow of changes in production
  • Select a reliable, cost-effective and hardened production deployment
  • Say guarantee SLAs while selling external APIs to 3rd parties
  • Ensure reliable and repeatable process of taking software from a source repository to an end user
Read case study
Performance Testing
  • Define and guarantee performance metrics in contracts with clients
  • Transparently measure defined SLAs between releases
  • Select a reliable, cost-effective and hardened production deployment
  • Say guarantee SLAs while selling external APIs to 3rd parties
  • Minimize application performance complaints
Read case study
Security Testing
  • Make sure that your system is safe and free from vulnerabilities
  • Verify that your system protects the data and maintains its intended functionality
  • Validate that application is fully compliant with a security standard like PCI DSS, ISO27001, HIPPA, GDPR
Read case study
Microservices
  • Provide guidance on micro-services architecture, design and technology
  • Establish an efficient development process for teams
  • Ensure deployment strategy is on par with delivery goals
  • Confirm that production infrastructure is reliable, cost-effective and hardened
Read case study
Data Processing Solutions
  • Handle massive quantities of data using batch and streaming approaches
  • Enhance existing successful data solutions to provide near real-time experience
  • Proactively react to incoming streams of data (alerts, fraud detection, etc.) in near real-time
Read case study

Consulting Case Studies

Microservices Migration
Microservices Migration - Performance testing
Data Processing
Automated Deployment Pipeline
Performance Testing
Data Science
Security Testing
System Audit

Talk To Us

Let’s talk about how Lohika can help you scale your engineering organization.
Email info@lohika.com