You're managing a complex system in the cloud. What tools can you use to make it more efficient?

Cloud monitoring needs to leverage cloud native tools. Organizations need to move beyond monitoring components to monitoring applications via synthetic transactions and availability from the Customer perspective. Not blinking lights

A. Tool should offer comprehensive monitoring of servers, databases, tools, and services through a SaaS-based data analytics platform (ex. Datadog) B. Tools should provide real-time insights into application performance, customer experience, and business success ( ex. New relic) C. Being a data analyst, we can make my own visualizations, but tools like Grafana can be used for analytics and interactive visualization.

Managing a complex system in the cloud requires a combination of tools to ensure efficiency, scalability, reliability, & and security. Here's a list of top tools but not limited to, which are commonly used for managing cloud systems. 1. Cloud Provider Management Console 2. Infrastructure as Code (IaC) Tools 3. Configuration Management Tools 4. Monitoring and Alerting Tools 5. Logging and Log Management Tools 6. Container Orchestration Tools 7. CI/CD Tools 8. Security and Compliance Tools 9. Performance Optimization Tools 10. Collaboration and Communication Tools By leveraging these tools effectively, you can streamline operations, improve efficiency, and ensure the smooth operation of complex systems in the cloud.

Indico usar CloudWatch da AWS. Monitora recursos e aplica??es em nuvem, com dashboards personalizáveis e alertas em tempo real. Monitora recursos de CPU, memória, rede, armazenamento e utiliza??o de disco de instancias EC2, Lambdas, RDS, S3 e outros servi?os AWS. Visualizar as métricas coletadas em gráficos e tabelas personalizáveis com vários estilos de visualiza??o. Configurar alarmes para notificá-lo quando as métricas excederem ou ficarem abaixo de limites predefinidos entre outros.

In my experience, monitoring is old. We need observabilty. We need to start measuring the user experience level (XLAs). We should establish traceability between the XLAs and resource utilization and bottlenecks. We should establish a comprehensive service mesh to help traceability.

Infrastructure as Code (laC) for automated provisioning, the preferred choice is Terraform, an open-source tools that allows us to define the cloud infrastructure in code for various service providers. For Oracle Cloud Infrastructure, ORacle Resource Manager is OCI’s native service. In case if someone uses AWS, AWS CloudFormation is an essential tool for defining resources in a structured template. For Azure, Azure Resource Manager (ARM) templates can be used.

In my experience, hosting an application on the cloud should be done after modernizing and working as microservices. Then, a release to a microservice should be fully automated with DevSecOps. Cloud resource, security, configuration management, application build, testing, releasing, and rollback should all be done using the "Everything as Code" practice. Then it is not automation, it is DevSecOps. This is the only way to manage the applications on the cloud so that their full potential is exploited. If the complex system still runs monolithic applications on IaaS, then there is no difference in running them on the cloud.

AWS Trusted Advisor, Azure Advisor, Google Cloud's Cost Management Tools: Description: Tools providing insights on resource usage, suggesting optimizations, and ensuring efficient resource provisioning. Benefits: Cost reduction, performance optimization, and improved resource utilization.

Testing comes with deployment, hence we need to consider CI/CD tools such as Jenkins, GitLab, Circle CI to name a few. If someone looks for the specialist then NUnit for C#, JUnit for Java, pyTest for Python, Mocca/Chai for JavaScript are few good tools. If someone looks for end-to-end then Selenium ( framework for automated web application testing across different browsers), alternatively Cypress can be used. Postman ( life of API developer will be miserable.. Swagger is an alternative).

Selenium, Junit, TestNG, Postman: Description: Essential testing tools for UI, unit, and API testing in cloud environments. Advantages: Automation for rapid error detection, maintaining system stability.

One thing I have found helpful is to adopt a good FinOps process. Right Sizing, Right placement, Right uptime, etc will help with continued optimization. I have also found it helpful to define the right observability implementation. The better we know the security, performance, and availability the right client experience can be delivered and optimal costs.

There are several tools to manage a complex system in the cloud and make it more efficient. CMPs:These are integrated products that provide for the management of public, private, and hybrid cloud env. Ex:RightScale,CloudCheckr IaC Tools:Terraform, Ansible, and Puppet can help automate create, update, and del resources in cloud env. Monitoring Tools: Datadog and New Relic can provide insights into your cloud systems' performance and help you identify any issues that might be affecting efficiency. Cloud Native Technologies: Kubernetes for container orchestration can greatly enhance the efficiency of cloud systems. Serverless: Lambda and Azure Functions allow running code without provisioning or managing servers which can simplify operations.

For Oracle customers OCI gives Oracle Cloud Advisor, OCI Performance Hub Spot.io is an alternative tool for the major cloud providers. Dynatrace, CloudHealth by VMWare are good alternatives

AWS Trusted Advisor, Azure Advisor, Google Cloud's Cost Management Tools: Description: Tools offering insights into resource usage, recommending optimizations, and ensuring efficient provisioning in cloud environments. Benefits: Cost reduction, performance optimization, and enhanced resource utilization.

For collaboration, it depends on the task in hand.. apart from the listed tools Microsoft Teams, Confluence, Figma, Lucidchart, adobe creative cloud, Asana are to name a few

- When evaluating collaboration tools for use in financial services, it's essential to ensure that they adhere to industry standards and regulations, such as GDPR or PCI DSS. Look for features like end-to-end encryption, access controls, and audit trails to safeguard sensitive information and maintain compliance. - Conducting thorough security assessments and vendor due diligence is imperative to mitigate risks associated with third-party tools. Verify the vendor's security practices, data handling procedures, and compliance certifications to ensure that the collaboration tools meet the stringent security requirements of the financial services industry.

Slack, Microsoft Teams, Jira: Description: Collaboration platforms enabling real-time communication, task tracking, and efficient project management in cloud development. Advantages: Transparency, improved team coordination, and support for agile development. Efficient communication is paramount in cloud development

DAO for Project Decision-Making: Implement a decentralized autonomous organization using blockchain for transparent, democratic project decision-making. Blockchain-Based CI Rewards: Integrate blockchain into CI to reward developers with tokens for quality code, creating a gamified, incentivized coding environment. AI Code Review Assistant: Develop an AI-driven code review assistant using NLP and ML to provide contextual feedback, improving code quality. VR Collaborative Coding: Explore real-time collaborative coding in virtual reality to enhance teamwork & creativity among developers. Voice-Driven Coding Assistant: Create a voice-driven coding assistant for hands-free interaction, improving developer productivity and user experience.