Security
Dynamic Scalablity
High Throughput
Real Time Event Based Processing
Straight Through Processing
Adherence to Applicable Compliance e.g. PCI-DSS, HIPAA, GDPR
Workflow Automation
Insightful Analytics
Seamless Integration with Legacy Systems
Integrated Deployments
Integrated Monitoring and Alerts
Test Automation
Load Based Infra Usage
AWS, Azure, GCP, Private Clouds
Python, NodeJS, Java, Go
React, Typescript, Javascript, HTML5, Flutter
React Native, Android, iOS
PostgresSQL, mySQL, SQL Server, MongoDB, DynamoDB
Redis, Memcache
RabbitMQ, SQS
Kafka, Spark
Kong, Zuul, AWS API Gateway
ECS, EKS, Docker, Kubernetes
Selenium, Appium, jMeter, Postman Collection, Saucelabs
GitHub, Bitbucket, Jenkins, Maven, Ansible, Docker, Terraform, AWS Code Pipeline
Slack, Sentry, ELK, Nagios, Prometheus, New Relic
Tableau, Domo, Power BI, Metabase
Hadoop, Hive, AWS EMR, Redshift, Athena, AWS S3
AWS S3, Azure Blob
Oozie, Airflow, Dbt, Talend, Sqoop, Spark
Elastic Search
We can help you collect, organize, and manage your data to ensure it is ready for analysis.
We can create custom dashboards and reports that help you understand and communicate insights from your data.
Our team can use advanced analytics techniques to uncover insights and trends in your data, and help you make data-driven decisions.
We can help you build and deploy machine learning models to predict future outcomes and make more accurate forecasts.
Our predictive analytics services can help you identify patterns and trends in your data to make better informed decisions.
There are a number of technologies that can be used to implement data lakes, data warehouses, and lakehouses. Some common technologies include:
Hadoop is an open-source framework that can be used to store and process large amounts of data. It is often used to implement data lakes and can be used in conjunction with other technologies like Spark for data processing.
Spark is an open-source data processing engine that can be used to perform distributed data processing tasks on large data sets. It can be used in conjunction with Hadoop to analyze data stored in a data lake.
Cloud storage platforms like Amazon S3 and Google Cloud Storage can be used to store large amounts of data in the cloud. These platforms are often used to implement data lakes.
Relational databases like MySQL, PostgresSQL, and SQL Server can be used to implement data warehouses. These databases are designed to store structured data and support fast query and analysis.
Data integration and ETL (extract, transform, load) tools can be used to move data from various sources into a data lake or data warehouse. These tools can also be used to clean, transform, and structure the data as needed.
Data warehousing platforms like Amazon Redshift, Snowflake and Google BigQuery can be used to implement data warehouses. These platforms are optimized for fast query and analysis of large data sets.
Data visualization tools like Tableau, Apache Superset, Qlik, and Power BI can be used to create charts, graphs, and other visual representations of data stored in a data lake, data warehouse, or lakehouse. These tools can help users understand and communicate insights from their data.
Allocating the computing resources and services that a cloud provider offers.
Tracking the performance and utilization of cloud-based services, such as storage, applications, and networks.
Configuring settings to ensure that the cloud environment is optimized for performance and reliability.
Ensuring that the cloud environment is secure from unauthorized access and malicious attacks.
Ensuring that the cloud environment is optimized for cost, performance, and efficiency.
Ensuring that the cloud environment is compliant with any applicable laws or regulations.
Establishing policies and procedures for effective and efficient management of the cloud environment.
Technology | Description |
---|---|
Version Control Systems | Version control systems like Git, SVN, GitHub, and Bitbucket help teams manage and track changes to code. |
Continuous Integration | Continuous integration tools like Jenkins, Travis CI, and CircleCI help teams automatically build and test code changes. |
Containerization | Containerization tools like Docker, Kubernetes, and AWS ECS help teams package and deploy applications in lightweight containers. |
Infrastructure as Code | Infrastructure as code tools like Terraform, CloudFormation, and Ansible help teams automate the provisioning and management of infrastructure. |
Configuration Management | Configuration management tools like Puppet, Chef, and Ansible help teams automate the configuration of servers and infrastructure. |
Monitoring and Logging | Monitoring and logging tools like Splunk, Elastic Stack, and AWS Cloudwatch help teams track the performance and health of applications and infrastructure. |
Cloud Platforms | Cloud platforms like AWS, Azure, and GCP provide a range of tools and services for building, deploying, and managing applications and infrastructure. |
Static Code Analysis Tools | Static code analysis tools like SonarQube, Veracode, and Checkmarx help teams identify vulnerabilities and security issues in code before it is deployed. |
Container Scanning Tools | Container scanning tools like Twistlock, Aqua Security, and Anchore help teams identify vulnerabilities and security issues in container images. |
Vulnerability | Vulnerability management tools like Qualys, Tenable, and Rapid7 help |
Management Tools | teams identify and prioritize vulnerabilities in applications and infrastructure |
Web Application Firewalls | Web application firewalls like Cloudflare, AWS WAF, and Imperva help protect against cyber threats by blocking malicious traffic to web applications. |
Network Security Tools | Network security tools like firewalls, intrusion detection and prevention systems, and virtual private networks (VPNs) help protect against cyber threats by monitoring and blocking malicious traffic to and from networks. |
Identity and Access Management (IAM) Tools | IAM tools like AWS IAM, Azure AD, and Google Cloud IAM help organizations manage and control access to resources and data. |
Compliance | Use Encryption and data masking techniques to adhere to PCI-DSS, HIPAA and other global security standards. Leverage tools like AWS KMS, Cloud HSM for generating and managing keys. |
UI Path, BluePrism, Open Span, Automation Anywhere
Python RPA Framework, PyPI, Request
Amazon Textract, Amazon Rekognition, Google Tesseract, Google Vision, Asprise, ABBYY
Beautiful Soup, Scrapy, Requests, Selenium
Selenium, Python RPA Framework, RPA Tools
Java, Python, UI Path, Other RPA Tools
Python Chatterbot, RPA Tools
Google Vision, Amazon Rekognition
Python, Nodejs Libraries
We will work with you to identify your business goals and develop a customized technical strategy to help you achieve them.
We will help you architect and design the platform, the technology stack and tools to be used, UI/UX design and scope down the MVP.
From concept to launch, we can help you bring your product ideas to life and get them to market quickly and efficiently.
Our team of skilled developers can help you build and optimize your platform, ensuring that it is scalable, reliable, and user-friendly.
We will help you identify and leverage growth opportunities, using data-driven approaches to drive traffic, engagement, and conversions.
The Lean Startup framework emphasizes rapid experimentation, iteration, and learning in order to identify and validate business models and achieve growth. It focuses on maximizing customer value and minimizing waste and risk.
Design Thinking is a human-centered approach to problem-solving that emphasizes empathy, creativity, and prototyping. It can be used to identify opportunities for innovation and develop solutions that meet the needs of customers and users.
Agile is a project management framework that emphasizes flexibility, collaboration, and continuous delivery. It is often used to manage complex, rapidly changing projects and can help accelerate the development and launch of new products and platforms.
The Customer Development framework focuses on identifying and validating customer needs and building a product or service that meets those needs. It emphasizes customer research, experimentation, and iteration in order to identify and validate business models.
The Lean Canvas is a planning tool that helps businesses map out their value proposition, customer segments, channels, revenue streams, and key resources and partners. It can be used to develop and refine a business model and identify growth opportunities.
Our manual testing services include functional testing, usability testing, compatibility testing, and more to ensure that your products and systems meet your quality standards.
Our automated testing services can help you save time and improve efficiency by automating repetitive or time-consuming testing tasks. We can help you set up and maintain automation testing frameworks using tools like Selenium, Appium, and TestComplete, UFT, Katalon, etc.
Our performance testing services can help you ensure that your products and systems can handle the expected load and performance demands. We can help you design and execute performance tests using tools like JMeter, LoadRunner, and NeoLoad, etc.
Our security testing services can help you identify and mitigate vulnerabilities in your products and systems. We can help you design and execute security tests using tools like Burp Suite, ZAP, and WebInspect, etc.
Our regression testing services can help you ensure that changes to your products and systems don't introduce new bugs or issues. We can help you design and execute regression tests to ensure ongoing quality and reliability.