Optimize your Python applications for peak performance
Get the most out of your Python applications with our performance and scalability audit tailored to your needs. Identify and eliminate bottlenecks, optimize resource usage, and ensure your system scales effortlessly – all to keep your applications running smoothly and efficiently.
Understanding software performance
Software performance refers to the responsiveness, stability, and efficiency of a software application under a specific workload.
Key performance metrics:
- Response time
- Throughput
- Resource utilization
Why is software performance important?
High-performing software ensures a seamless user experience, leading to greater user satisfaction, higher retention rates, and improved overall efficiency. Conversely, poor performance can cause frustration, decrease productivity, damage a company’s reputation, and ultimately result in significant revenue loss.
User satisfaction
Users expect applications to be fast and responsive. Even a slight delay can lead to dissatisfaction.
Bussiness revenue
Performance issues can directly impact sales and conversions. For instance, a slow e-commerce site may deter potential customers.
Competitive advantage
Applications that perform well stand out in the market, giving businesses an edge over competitors.
Scalability
Efficient performance ensures that applications can handle increased loads as the user base grows.
Performance boost benefits
Faster load times & Better user experience
- Improve response times by up to 80%, making your website or application feel much faster
- Reduce delays in loading pages, which keeps users happy and engaged
Source: arXiv, “A study of HTTP/2’s Server Push Performance Potential”
Lower cloud & infrastructure costs
- Cut down on unnecessary computing power and memory usage, saving you 30-50% on cloud expenses
- Optimize your cloud setup to ensure you’re only using what you need, and speed up processes with smart caching
Source: arXiv, “Cloud Instance Management and Resource Prediction For Computation-as-a-Service Platforms”
Prevent downtime & failures
- Fix issues before they cause crashes or slowdowns, keeping your system running smoothly
- Ensure your system can easily handle a sudden increase in users or data
Prepare for future growth
- Design your system to grow quickly without increasing costs too much
- Test your system under heavy loads to make sure it can handle more users and data as your business expands
Performance boost checklist
Does your software need a performance boost? Identify your challenges with this quick checklist.
Slow response time
If pages, reports, or APIs take too long to load, it’s a sign of inefficiencies in code, database queries, or server resources.
Frequent timeouts and errors
If users experience timeouts, crashes, or “server not responding” messages, the system may be struggling to handle requests efficiently.
Scalability issues
If performance degrades significantly when more users or data are added, your system may need better database indexing, caching, or load balancing.
Poor user experience
If users frequently complain about lag, delays, or sluggish performance, it’s a strong signal that optimizations are needed.
Benchmark comparisons
If your competitors’ or industry-standard systems perform significantly better, it may be time for a performance audit.
Need help with that?
Let us assist you in identifying your needs and selecting the best solution.
Why focus on Python's performance?
No.
1
most popular language. Python’s popularity has surged in recent years, becoming the most used language on GitHub, overtaking JavaScript after a 10-year run.
Source: GitHub, “Octoverse: AI leads Python to top language as the number of global developers surges”
Over
54%
of developers utilize Python for data analysis, and 46% of them select it as their go-to web development language. Its versatility makes it a top choice across multiple domains.
Source: Statista, “Reasons for using Python worldwide in 2022”
Performance challenges
While Python offers numerous advantages, it also comes with challenges, particularly in performance. Benchmarks show that its efficiency can vary significantly based on implementation and workload.
These insights underscore the importance of optimizing Python applications to achieve performance levels comparable to more efficient languages.
Our 4 weeks performance approach
Step I: Gathering Requirements
Step II: Instance Setup
Step III: Analysis & Fixes
Step IV: Report & Recommendations
Step I: Gathering requirements
- Understanding your project scope & business needs
- Collaborating with you to define objectives and performance expectations
- Identifying key business drivers and specific requirements for the audit
- Preparing complex time estimations based on requirements
- Assembling the audit team
- Forming a dedicated team with the necessary expertise for the audit process
- Ensuring the team is aligned on project goals and timelines
- Conducting an initial Q&A session with you
- Hosting a session to clarify any questions and understand your priorities
- Aligning expectations and gathering crucial information for the audit
- Gaining access to systems, logs, & performance data
- Securing necessary permissions to access critical systems, logs, and performance data
- Ensuring compliance with security protocols while gathering relevant data for analysis
- Ready for the next step!
Step II: Instance setup
- Creating a test instance
- Setting up a dedicated environment to simulate real-world conditions
- Ensuring the instance mirrors the production system for accurate testing with specific parameters like RAM and CPU
- Feeding instance with relevant data
- Populating the test instance with real or simulated data to reflect actual usage scenarios
- Ensuring data integrity for reliable performance testing
- Installing performance monitoring frameworks
- Implementing tools to track and measure system performance in real-time
- Identifying bottlenecks and inefficiencies through detailed monitoring
- Ensuring secure access & compliance
- Configuring secure access protocols to safeguard sensitive data
- Ensuring all testing complies with relevant security standards and regulations
- Ready for the next step!
Step III: Analysis & Fixes
- Code-level performance profiling
- Identifying inefficient loops, excessive object allocations, and Python-specific inefficiencies
- Optimizing memory management and garbage collection (GC) for better resource efficiency
- Database & query optimization
- Fixing slow queries and improving database indexing
- Optimizing ORM (Object-Relational Mapping) performance, like with Django ORM, for up to 10x faster queries
- Scalability & load testing
- Simulating high-traffic scenarios to uncover potential bottlenecks
- Optimizing concurrency and thread management for more efficient handling of simultaneous requests
- Cloud & infrastructure efficiency
- Preparing right-size cloud resources to avoid unnecessary costs
- Implementing caching solutions to reduce load times by up to 40%
- Security & reliability enhancements
- Addressing memory leaks and preventing crashes
- Strengthening system resilience with auto-scaling and disaster recovery strategies
- Ready for the next step!
Step IV: Report & Recommendations
- Comprehensive audit report
- Presenting a detailed analysis of the system's current performance
- Identifying critical areas that require attention for optimal performance
- Key focus areas for improvement
- Highlighting areas with the most significant potential for future enhancements
- Outlining specific targets for improving system efficiency
- Recommendations for ongoing optimization
- Providing actionable insights to maintain long-term system health
- Suggesting strategies for continuous performance improvement
- Final Q&A session
- Hosting a session to discuss the audit findings in detail
- Addressing any questions and outlining the next steps for implementation
- Your performance fully boosted!
“…Throughout our partnership, SolDevelo consistently demonstrated exceptional technical expertise, professionalism, and a deep commitment to delivering high-quality solutions. Their team showcased remarkable problem-solving skills and a proactive approach to addressing challenges, ensuring that project milestones were met on time and within scope…”
Dragos Dobre
IT Systems Architect / Project Leader
Digital Health Unit
Swiss Centre for International Health
Swiss TPH
What's included in the audit report?
- Identified performance issues
A detailed breakdown of bottlenecks, inefficiencies, and problem areas in your Python application.
- Root cause analysis
Insights into what caused the performance challenges and their impact on the system.
- Benchmark results
Before-and-after performance comparisons based on our testing and optimization efforts.
- Actionable next steps
A prioritized list of improvements for developers and infrastructure teams to implement.
- Optimization strategies
Recommendations on how to improve code efficiency, database performance, and system scalability.
- Future scalability plan
A roadmap for ensuring the application remains performant as traffic and data volumes grow.
- Security & compliance considerations
Any identified risks and best practices for maintaining performance without compromising security.
Client stories
Read more about our experience in performance testing and optimization.
openIMIS
Performance audit
We conducted a comprehensive performance audit of openIMIS to identify and address system bottlenecks. By developing and executing JMeter scripts to simulate various load scenarios, we assessed the system’s stability and responsiveness under different conditions.
openIMIS
95% performance boost
Using the insights gathered during the audit, we improved openIMIS’s performance by over 95% in less than a week. Our team swiftly implemented significant enhancements, optimizing system efficiency and responsiveness.
Technology stack
Python is a versatile language for building software, automating tasks, and integrating systems. Tools like Django Silk enhance performance with profiling, SQL analysis, and monitoring.
Apache JMeter is used to test system performance. It helps simulate multiple users interacting with software to identify potential weaknesses before they affect real users.
Gradle helps automate and speed up the process of building and updating software. It ensures that all necessary components are correctly assembled so that applications run smoothly.
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