Cloud vs Non-Cloud Project Management

A professional who designs and implements the technical architecture of a software solution, ensuring it meets business needs and technical requirements.

A professional who understands the functional needs of a business and translates them into software requirements and specifications.

A professional who leads and guides a team of developers, ensuring the timely and successful completion of a project.

A professional who oversees the technical aspects of a project, ensuring that the solution aligns with the specified architecture and technical requirements.

A professional who works closely with clients to understand their needs and propose effective solutions.

Using computer science principles and techniques to analyze and extract meaningful patterns from large datasets.

A branch of mathematics that deals with optimizing resource allocation and decision-making under constraints.

A programming language used for statistical computing and graphics., often used for data analysis in data-mining and operations research

A unique identifier used to track a specific request or operation across different system components.

A log message indicating that the system has successfully completed an analytics process.

A log message displaying information about a payment attempt that was unsuccessful but will be retried later.

A log message displaying information about an event that has occurred, such as a request being initiated or a notification being sent.

A log message displaying information about a low-level action taken within the system, for debugging or tracing purposes.

A log message that provides a concise summary of the event that occurred.

A specific component or service that is responsible for performing a particular task within the system, such as handling analytics, shipping, or user profile management.

A log message with the severity level "INFO" indicating a routine event or successful operation in the system.

A log message with the severity level "DEBUG" providing detailed information about the internal workings of a program or process.

A log message with the severity level "WARN" indicating a potential problem or an unusual situation that warrants attention but doesn't necessarily lead to immediate failure.

A log message with the severity level "ERROR" indicating a critical failure in the system that prevents normal operation.

A timestamp that captures the exact time and date when a log message was generated. It helps with troubleshooting by providing context about when an event occurred.

A tag or identifier that specifies the origin or source of a log message. It helps in identifying which part of the application generated the message.

A structured record of events or activities that occur within a software system. Logs provide insights into the application's behavior and help diagnose and resolve issues.

A message with the severity level "DEBUG" indicating a routine event or successful operation in the system.

A message in the log indicating something unexpected or potential problems.

A message in the log indicating a failure in the system.

The time and date of a recorded event.

A record of the location or origin of a log message.

A sequential record of activities and events related to an application or system.

Debugging and troubleshooting activities that focus on the application's logs to understand why something went wrong.

An open-source tool for visualizing and monitoring data from various sources (like Prometheus or InfluxDB). It's used to create interactive dashboards and graphs, helping track performance and analyze system behavior.

A data analytics platform that excels at collecting, indexing, and visualizing machine data from applications, servers, and IT systems. It's used for security, IT operations, and business intelligence.

A process of actively monitoring and managing the health, performance, and behavior of systems, applications, and services. It utilizes various tools and techniques to ensure optimal functioning and identify potential issues.

Numerical values that represent a specific aspect of a system or application. They provide insights into performance, resource usage, or other key metrics.

Warnings or notifications triggered when a system or application deviates from expected behavior or performance thresholds. They alert teams to potential problems requiring attention.

A crucial aspect of observability that involves tracking and analyzing system and application performance over time. This helps understand trends, identify bottlenecks, and optimize performance.

A comprehensive approach to understanding system behavior and performance, encompassing metrics, logs, and traces to offer a holistic view of the system's state.

A system or process that systematically gathers, analyzes, and interprets data about system events, user interactions, and application behavior. This data is used to diagnose issues, understand user patterns, and improve system performance.

In non-cloud projects, infrastructure is treated as unique and irreplaceable, like pets. When issues arise, they are addressed individually. In contrast, cloud projects view infrastructure as interchangeable and replaceable, like cattle. When issues occur, failing instances are simply replaced.

Cloud projects emphasize scalability and consistency, prioritizing functionality over unique configurations. Instead of focusing on individual instances, they focus on having enough resources of the same type.

Cloud projects aim for minimal dependence on the local environment, focusing on the overall result. This means that cloud services are typically more portable and adaptable.

In the shared responsibility model for cloud services, the cloud provider is responsible for the security of the underlying infrastructure, while the client is responsible for the security of data and applications running on it.

The shared responsibility model emphasizes the importance of understanding and fulfilling security obligations within the cloud environment. This involves a clear division of responsibilities for securing different layers of the cloud infrastructure.

Each microservice should be able to function independently and handle its own responsibilities without relying on other services.

Testing how microservices interact with each other to ensure they can communicate and work together as a cohesive unit.

A process that automatically builds and tests code changes, ensuring maintainable code quality.

Creating detailed documentation for each microservice, including API specifications and usage guidelines for developers.

Creating a system where each service is responsible for a specific, well-defined task.

Using software tools to automatically test various aspects of a microservice, helping to identify potential issues early on.

A strategy where software applications are broken down into smaller, independent services, allowing for easier development, deployment, and scaling.

Ensuring that all the microservices within a system communicate and interact effectively with each other.

A set of guidelines and best practices for creating and managing microservices within a system.

A monolithic application is a single-tiered software application where different modules are combined into one program. It's like having all the parts of a car in one giant box.

Microservices allow for independent development, deployment, and scaling of smaller services, each focused on a specific function. Imagine having separate teams build car parts instead of one team building the entire car.

Each microservice should work independently, have its own data, and be able to scale separately. It's like having a team dedicated to building car doors, working independently from the engine team.

Monolithic applications are difficult to scale because changes require updating the entire application. Imagine scaling up a single, large car engine instead of separate components.

Monolithic applications are difficult to update since any change requires redeploying the entire application. Imagine updating the whole car every time you want to fix a single part!

With microservices, each service can be deployed independently. This allows for faster updates and less disruption to the overall system. Imagine updating a car door without affecting the engine.

Monolithic applications are difficult to fix quickly, since an error in one part can impact the entire system. Imagine a single fault causing the entire car to stop working!

Microservices allow for easier debugging and fixing of errors because individual services can be isolated and fixed. Imagine fixing a faulty car door without affecting the engine.

A design pattern that helps prevent cascading failures in a system by isolating failing services and allowing for recovery. When a service experiences repeated failures, the circuit 'opens,' stopping requests to that service. Once stability is checked, the circuit 'closes,' resuming normal operations.

A strategy used to handle service failures by retrying operations after a delay. The delay can be fixed, incremental, or exponential, depending on the system's needs. Retries increase the chance of success by allowing for temporary issues to resolve.

An intermediary system that manages and distributes events between producers and consumers. It decouples the two, allowing for asynchronous communication and event-driven architectures. Producers don't need to know about specific consumers, and vice-versa.

A software development approach that focuses on dividing complex systems into smaller, self-contained units called 'bounded contexts.' Each context represents a distinct business domain, improving flexibility, scalability, and maintainability.

A collection of related services that work together to achieve a specific business goal. They share a common language and data model, ensuring consistent understanding within the context.

The process of testing how microservices interact with each other to ensure they can communicate and work together as a cohesive unit. This is crucial for ensuring that the system functions as a whole.

The process of integrating and testing code changes frequently and automatically. It ensures code quality, reduces integration issues, and allows for continuous delivery of software updates.

A cloud deployment model where resources are hosted in a private datacenter, offering control over the entire environment and its infrastructure.

A combination of public and private clouds, allowing organizations to leverage both public cloud services and their own private infrastructure.

A cloud deployment model where resources are hosted in public data centers and offered as a service to multiple customers. Think Amazon Web Services (AWS) or Google Cloud Platform.

Defined as independent, independently runnable, and deployable software units. They represent a specific business capability and can be developed, deployed, and scaled independently.

Analyzing a monolithic application to identify distinct business functionalities and modules that can be separated into individual services.

Determining the specific responsibilities and boundaries for each microservice, ensuring clear separation of concerns.

Deciding how data will be shared between microservices, potentially requiring data replication, synchronization, or separate databases.

Choosing communication protocols and APIs for microservices to interact with each other, such as RESTful APIs or messaging queues.

Creating individual codebases for each microservice, either as separate repositories or as packages within a monorepo.

Dividing the database used by the monolithic application into smaller databases or schemas, to improve isolation and scalability of services.

Developing the specific business logic and functionalities that each microservice is responsible for.