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AWS DMS implementation guide: Building resilient database migrations through testing, monitoring, and SOPs

AWS Database Migration Service (AWS DMS) simplifies database migration and replication, offering a managed solution for customers.
Investing time in proactive database migration planning yields substantial returns by minimizing disruptions and achieving better migration outcomes.
This post provides proactive measures for optimizing AWS DMS implementations from the initial setup phase, focusing on planning, failure testing, SOPs, monitoring, and the AWS Well-Architected Framework.
Conducting a proof of concept (PoC) helps in identifying issues early and estimating migration time and resource commitments.
Systematic failure testing is crucial for maintaining business continuity and developing SOPs to address system disruptions.
Monitoring and alerting play a key role in maintaining seamless replication operations and promoting data integrity during migration.
AWS DMS provides various monitoring features like CloudWatch metrics, logs, and time travel logs for effective monitoring and reporting.
Establishing comprehensive contingency plans, setting up CloudWatch alarms, and using Well-Architected Framework principles contribute to designing reliable cloud architectures.
The post emphasizes the importance of developing customized migration strategies aligned with unique use cases to ensure long-term success in data movement strategies.
Authors include Sanyam Jain, a Database Engineer, Sushant Deshmukh, a Senior Partner Solutions Architect, and Alex Anto, a Data Migration Specialist Solutions Architect.

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Dev

231

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How to Upgrade BizTalk Send Port from SQL to WCF-SQL?

Upgrading your BizTalk application from an SQL send port to a WCF-SQL send port can be challenging, especially concerning schema compatibility.
Transitioning to WCF-SQL offers more functionalities such as better error handling and support for multiple message formats but requires careful schema management.
To upgrade, configure the new WCF-SQL port, set up the SOAP Action header correctly, ensure XML conformity, and test the port while watching out for common issues.
Ensure that XML aligns with the schema, verify parameter matches, handle namespace conflicts, and debug SOAP Action problems effectively to successfully complete the transition.

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Medium

410

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What’s a database anyway?? A blog post for kids

A database is something everyone uses to organize and retrieve information, like searching for a book at the library or browsing TV shows.
Our minds also function like databases, storing memories based on importance and allowing quick access to information.
Human minds excel at language understanding, while machines require precise instructions in a database language to function efficiently.
Database languages bridge the gap between human communication and machine comprehension, ensuring accurate data processing.
Thinking like a database, assigning values and criteria to choices, can improve decision-making and understanding others' perspectives.
Utilizing database principles can enhance problem-solving skills and lead to better interpersonal relationships.
In a fun analogy, planning a camping trip using database-like thinking can help select the most suitable campsite based on predefined criteria.
Database queries, when formulated correctly, provide accurate responses and can adapt easily to changes in data.
Understanding databases simplifies their function and showcases how structured data management improves decision-making processes.
Database interaction fosters critical thinking skills and enhances analytical abilities, contributing to more effective problem-solving.

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Medium

290

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Implementation of an E-Commerce System on AWS in an automated way using Terraform and Ansible

Infrastructure for an E-Commerce system was provisioned on AWS using Terraform and Ansible.
Designed architecture with single VPC, public and private subnets, EC2 instance, RDS, and Redis.
Provisioned infrastructure with Terraform using modules for VPC, Compute, Database, and Security Groups.
Configured EC2 instance with Ansible for system updates, software installations, Magento setup, and optimization.

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Siliconangle

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Power-hungry clouds: Inside tech’s most expensive quarter

The current quarter's earnings reports reveal that demand is not the primary constraint for hyperscale clouds, but rather the limitations of physics, such as power availability and GPU scarcity, are now critical factors.
Major players like Amazon Web Services, Microsoft, and Google are investing heavily in capital expenditures, totaling around $63 billion, to meet the growing demand for compute-intensive AI models.
The focus has shifted to power availability as the key factor influencing hyperscaler growth, with sustainable energy footprints, GPU allocation, and margin-accretive AI services playing pivotal roles.
Microsoft, AWS, and Google continue to demonstrate strong growth in their infrastructure and platform revenue despite macroeconomic challenges, emphasizing the importance of power and GPU scarcity in infrastructure expansion.
AWS maintains impressive operating margins close to 40%, driven by its custom-silicon innovations like Graviton and Trainium 2, while Microsoft and Google are also making strides in their cloud offerings.
Google Cloud is showing momentum in core infrastructure growth, leveraging its TPU roadmap, but struggles with lower operating margins and ongoing supply bottlenecks compared to AWS and Azure.
The Big Three U.S. hyperscalers, including AWS, Azure, and Google Cloud, are projected to surpass $245 billion in revenue by 2025, with Azure showing accelerated growth driven by AI services.
Despite challenges like power shortages and margin pressures, the cloud industry remains resilient, with Azure, AWS, and Google Cloud continuing to attract investment and prioritize cloud spending.
ETR spending momentum data indicates that cloud remains a key budget priority for CIOs, with Azure leading in account penetration, AWS maintaining high adoption rates, and Google Cloud rapidly expanding its footprint.
The future outlook for the cloud industry includes monitoring AI adoption, power constraints, custom silicon development, hybrid sovereignty trends, public policy impacts, and China's influence on the global cloud market.
Investors and businesses are advised to track industry trends, make informed decisions on cloud adoption, and stay abreast of the evolving landscape as the hyperscalers navigate through power challenges and innovate in AI and infrastructure.

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Hackernoon

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Best Practices for Faster Queries: A SQL Performance Tuning Tutorial

Efficient SQL queries are crucial for optimal performance in Oracle databases. This tutorial focuses on key practices for query optimization tailored for Oracle environments.
Utilizing indexes effectively, avoiding functions on indexed columns, using Oracle's execution plans, implementing bind variables, partitioning large tables, utilizing materialized views, and monitoring query performance with AWR are essential best practices highlighted.
Key practices include creating appropriate indexes to speed up data retrieval, avoiding functions on indexed columns for efficient index usage, using bind variables to reduce parsing and improve plan reuse, partitioning large tables to enhance performance, and using materialized views for complex queries.
By implementing these best practices, Oracle database users can optimize SQL queries, reduce execution time, and improve overall database performance, leading to significant enhancements in query efficiency.

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Dev

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How to install PostgreSQL on macOS: Step-by-Step Instructions

To install PostgreSQL on macOS, you can use Homebrew which is recommended.
Start by installing Homebrew if you haven’t already, then install PostgreSQL and start the PostgreSQL service.
After installing, initialize the database if needed and verify the installation using psql --version.
You can create a new database and user using PostgreSQL CLI and browse PostgreSQL data using psql CLI or GUI Clients like DBeaver, pgAdmin, or TablePlus.

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Dev

210

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DuckDB: When You Don’t Need Spark (But Still Need SQL)

DuckDB is an open-source, in-process SQL OLAP database designed for analytics and runs embedded inside applications.
DuckDB achieves high performance through columnar storage and vectorized execution, handling complex analytical queries efficiently on a single machine.
It dynamically manages memory and disk usage, supports in-memory mode, out-of-core mode, hybrid execution, and persistent storage.
DuckDB is praised for local dataset exploration, CI and pipeline testing without Spark, batch transformations, and lightweight production workflows.

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Medium

299

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Why uber ditched postgres for mysql: What every developer can learn from it

Uber transitioned from PostgreSQL to MySQL as its database solution due to PostgreSQL's limitations with scale and performance as the company grew.
PostgreSQL faced issues such as index bloat, replication challenges, and complex upgrade paths as Uber's platform expanded globally.
MySQL was chosen for its simpler replication model, better scalability, and flexibility in handling evolving data needs at Uber's scale.
Uber's custom Schemaless system was built on top of MySQL to provide real-time consistency, easier upgrades, and enhanced tooling for operations.
MySQL's simpler replication system, ease of upgrades, and compatibility with containerized services made it a better fit for Uber's needs.
The switch from PostgreSQL to MySQL was not about one being better than the other, but about choosing the right tool for the evolving requirements.
Uber's migration sparked discussions in the developer community on database choices and the importance of selecting tools based on specific needs rather than trends.
The focus on monitoring, metrics, and internal tooling helped Uber identify bottlenecks and adapt their database solution for improved performance.
Uber's approach emphasized building fast, observing early, and refactoring continuously to optimize for scale and operational efficiency.
The key takeaway is to prioritize what works best for the problem at hand, rather than sticking to popular choices, especially when scaling operations.
Choosing the right database solution involves considering trade-offs and aligning tools with the specific requirements and growth trajectory of the organization.

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Amazon

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Understanding transaction visibility in PostgreSQL clusters with read replicas

The article discusses transaction visibility behavior in PostgreSQL clusters with read replicas, as highlighted in a Jepsen report on Amazon RDS for PostgreSQL Multi-AZ clusters.
The issue of transactions becoming visible in a different order in primary and replica clusters is a known long-standing problem in the PostgreSQL community.
This behavior, known as the Long Fork anomaly, is a violation of Snapshot Isolation and has been acknowledged since at least 2013.
The Long Fork anomaly affects the order in which transaction effects become visible in PostgreSQL, leading to potential discrepancies in application behavior.
The article provides an example scenario to illustrate how the Long Fork anomaly can impact the visibility of transaction effects in PostgreSQL clusters with read replicas.
Various solutions have been proposed to align the visibility order with the commit order by using Commit Sequence Numbers (CSNs) in PostgreSQL.
Although the Long Fork anomaly is esoteric from an end-user perspective, fixing it is crucial for enhancing enterprise-grade capabilities in PostgreSQL clusters.
The article emphasizes the importance of addressing the Long Fork anomaly, particularly in scenarios related to distributed systems, query routing, data synchronization, and point-in-time restore.
AWS is dedicated to PostgreSQL's success, actively contributing to the PostgreSQL community and working towards resolving the Snapshot Isolation anomaly in PostgreSQL.
Recommendations for users include reviewing application assumptions, using explicit synchronization mechanisms, and contacting AWS Support for deployment concerns.

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Dev

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🚀 Oracle E-Business Suite R12.2: Adding and Removing Application Tier Nodes

Oracle E-Business Suite (EBS) Release 12.2 introduces a dual file system architecture with online patching.
To add a secondary node to R12.2, prepare files from the primary application tier, create tar archive, transfer, unpack, and prepare the new node.
Prepare pairs file for node-specific configurations and clone the secondary node for context instantiation, registering WebLogic managed servers, and starting relevant services.
For removing an application tier node in R12.2, execute adProvisionEBS with necessary options and considerations like backups, post-clone validations, AutoConfig runs, NTP clock synchronization, and monitoring practices.

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Amazon

129

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Graph-powered authorization: Relationship based access control for access management

Relationship-based access control (ReBAC) is introduced as an alternative to traditional authorization systems like role-based access control (RBAC) and attribute-based access control (ABAC) for enterprise scale authorization.
ReBAC architecture uses Amazon Neptune to create a knowledge graph for managing billions of relationships and processing millions of requests per second.
Challenges like role explosion and token bloat are addressed by ReBAC by focusing on relationships between users and resources instead of roles or attributes.
RBAC assigns permissions to roles and faces challenges with role explosion, whereas ABAC makes access decisions based on attributes and can be complex to manage.
ReBAC determines access based on relationships, modeling them as a graph with nodes and edges for intuitive access patterns mirroring real-world relationships.
Neptune and ReBAC systems complement each other, with Neptune handling relationship modeling efficiently and ReBAC ensuring fine-grained access control in real time.
ReBAC offers millisecond latency, scalability, and reliability, and can be implemented through custom solutions, open-source tools, or managed services like OktaFGA or AuthZed.
Entitlements in industries like financial services and healthcare benefit from ReBAC by dynamically controlling data access based on subscription levels or agent profiles.
ReBAC transformation of access management simplifies administrative work, reduces errors, and scales effectively by automating access levels based on relationships.
By integrating ReBAC with Amazon Neptune, organizations can optimize performance and minimize duplication for efficient and flexible access control.

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Dev

403

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Level Up Your Data Skills: 10 Essential SQL Books for Devs & Data Scientists

SQL (Structured Query Language) is crucial for Software Engineers, akin to system design and coding.
Knowledge of SQL is essential for programmers regardless of their main programming language.
Proficiency in SQL is highly valued by interviewers and essential for full-stack developers.
The article discusses the significance of learning advanced SQL concepts beyond basic queries.
It provides a list of 10 recommended SQL and database books for software engineers.
Books like 'Head First SQL' and 'SQL QuickStart Guide' are recommended for beginners.
Practical SQL, SQL Antipatterns, and other books focus on advanced SQL programming and data analysis.
SQL Performance Explained and SQL for Data Analysis offer insights into query optimization and data transformation.
'SQL for Smarties' and 'Learning SQL' are suggested for improving SQL query skills and data manipulation.
Overall, mastering SQL is challenging but essential, and these books can help software engineers on their SQL journey.

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Hackernoon

398

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SQL Recursive Queries - How to Understand Common Table Expressions (CTEs)

Recursive queries in SQL, enabled by Common Table Expressions (CTEs), allow working with hierarchical or recursive data structures like employee-manager relationships, family trees, or file directories.
A Common Table Expression (CTE) is a temporary result set defined within a WITH clause that improves query readability and is useful for recursive operations.
Common situations to use CTEs include breaking down complex queries into manageable parts, reusability within the same query for improved performance, creating temporary results without additional tables, and enhancing query readability.
CTEs simplify SQL query writing, especially for recursive operations, hierarchical data, and complex logic breakdown, offering powerful features for data-related insights.

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Hackernoon

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SQL Transactions - How to Implement COMMIT, ROLLBACK, and Savepoints With Python

Tools like DataGrip simplify transaction handling by offering graphical interfaces for commit, rollback, and savepoints.
In SQL, COMMIT finalizes changes, ROLLBACK reverts transactions, and SAVEPOINT allows partial rollbacks.
Python libraries like cx_Oracle, mysql-connector-python, psycopg2 enable explicit transaction controls.
Transactions involve starting, executing SQL statements, committing or rolling back changes, and using savepoints for finer control.

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