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Presented on JavaDay Kyiv 2014 conference.
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Devroom: https://fosdem.org/2016/schedule/track/mysql_and_friends/
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Second Skin: Real-Time Retheming a Legacy Web Application with Diazo in the C...Chris Shenton
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MongoDB .local Bengaluru 2019: New Encryption Capabilities in MongoDB 4.2: A ...MongoDB
Many applications with high-sensitivity workloads require enhanced technical options to control and limit access to confidential and regulated data. In some cases, system requirements or compliance obligations dictate a separation of duties for staff operating the database and those who maintain the application layer. In cloud-hosted environments, certain data are sometimes deemed too sensitive to store on third-party infrastructure. This is a common pain for system architects in the healthcare, finance, and consumer tech sectors — the benefits of managed, easily expanded compute and storage have been considered unavailable because of data confidentiality and privacy concerns.
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This presentation:
* covers basics of caching and popular cache types
* explains evolution from simple cache to distributed, and from distributed to IMDG
* not describes usage of NoSQL solutions for caching
* is not intended for products comparison or for promotion of Hazelcast as the best solution
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Presented on JavaDay Kyiv 2014 conference.
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Devroom: https://fosdem.org/2016/schedule/track/mysql_and_friends/
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MongoDB .local Bengaluru 2019: New Encryption Capabilities in MongoDB 4.2: A ...MongoDB
Many applications with high-sensitivity workloads require enhanced technical options to control and limit access to confidential and regulated data. In some cases, system requirements or compliance obligations dictate a separation of duties for staff operating the database and those who maintain the application layer. In cloud-hosted environments, certain data are sometimes deemed too sensitive to store on third-party infrastructure. This is a common pain for system architects in the healthcare, finance, and consumer tech sectors — the benefits of managed, easily expanded compute and storage have been considered unavailable because of data confidentiality and privacy concerns.
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* covers basics of caching and popular cache types
* explains evolution from simple cache to distributed, and from distributed to IMDG
* not describes usage of NoSQL solutions for caching
* is not intended for products comparison or for promotion of Hazelcast as the best solution
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Security mechanisms, such as user and network access control and policies in Openshift and underlying Openstack, the audit trail of administrative actions, ways to use and protect Kubernetes secrets, and the concealment of application data.
How to address technical limitations or potentially unknown vectors of attack using compensating controls via auditd, monitoring, and alerting.
Security practices in Docker containers.
Use OpenSCAP auditing tool and profiles to audit virtual machine (VM) hosts and container images in our release pipeline.
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Speakers: Phil Christensen, Sr. DevOps Engineer, Solutions Architect
Phil is an open source software engineer and cloud solutions architect with 15+ years of experience. He focuses on Puppet automation, containers, and Amazon Web Services infrastructure and holds all five AWS Certifications.
If you are interested in learning more about Logicworks' unique approach to cloud migration and management, contact us or talk to a cloud expert at (212) 625-5300.
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Where is my cache architectural patterns for caching microservices by example
1. Where is my cache?
Architectural patterns for caching
microservices by example
Rafał Leszko
@RafalLeszko
rafalleszko.com
Hazelcast
2. About me
● Cloud Software Engineer at Hazelcast
● Worked at Google and CERN
● Author of the book "Continuous Delivery
with Docker and Jenkins"
● Trainer and conference speaker
● Live in Kraków, Poland
3. About Hazelcast
● Distributed Company
● Open Source Software
● 140+ Employees
● Products:
○ Hazelcast IMDG
○ Hazelcast Jet
○ Hazelcast Cloud
@Hazelcast
www.hazelcast.com
15. ● No Eviction Policies
● No Max Size Limit
(OutOfMemoryError)
● No Statistics
● No built-in Cache Loaders
● No Expiration Time
● No Notification Mechanism
Java Collection is not a Cache!
18. Caching Application Layer
@Service
public class BookService {
@Cacheable("books")
public String getBookNameByIsbn(String isbn) {
return findBookInSlowSource(isbn);
}
}
19. Caching Application Layer
@Service
public class BookService {
@Cacheable("books")
public String getBookNameByIsbn(String isbn) {
return findBookInSlowSource(isbn);
}
}
Be Careful, Spring uses ConcurrentHashMap by default!
29. Embedded Cache
Pros Cons
● Simple configuration /
deployment
● Low-latency data access
● No separate Ops Team
needed
● Not flexible management
(scaling, backup)
● Limited to JVM-based
applications
● Data collocated with
applications
48. @Configuration
public class HazelcastCloudConfiguration {
@Bean
CacheManager cacheManager() {
ClientConfig clientConfig = new ClientConfig();
clientConfig.getNetworkConfig().getCloudConfig()
.setEnabled(true)
.setDiscoveryToken("KSXFDTi5HXPJGR0wRAjLgKe45tvEEhd");
clientConfig.setGroupConfig(
new GroupConfig("test-cluster", "b2f984b5dd3314"));
return new HazelcastCacheManager(
HazelcastClient.newHazelcastClient(clientConfig));
}
}
Cloud (Cache as a Service)
50. Client-Server (Cloud) Cache
Pros
● Data separate from
applications
● Separate management
(scaling, backup)
● Programming-language
agnostic
Cons
● Separate Ops effort
● Higher latency
● Server network requires
adjustment (same region,
same VPC)
54. Sidecar Cache
Similar to Embedded:
● the same physical machine
● the same resource pool
● scales up and down together
● no discovery needed (always localhost)
Similar to Client-Server:
● different programming language
● uses cache client to connect
● clear isolation between app and cache
55. @Configuration
public class HazelcastSidecarConfiguration {
@Bean
CacheManager cacheManager() {
ClientConfig clientConfig = new ClientConfig();
clientConfig.getNetworkConfig()
.addAddress("localhost:5701");
return new HazelcastCacheManager(HazelcastClient
.newHazelcastClient(clientConfig));
}
}
Sidecar Cache
57. Sidecar Cache
Pros Cons
● Simple configuration
● Programming-language
agnostic
● Low latency
● Some isolation of data and
applications
● Limited to container-based
environments
● Not flexible management
(scaling, backup)
● Data collocated with
application PODs
72. Reverse Proxy Sidecar Cache
#!/bin/bash
# Forward TCP traffic on port 80 to port 8000 on the eth0 interface.
iptables -t nat -A PREROUTING -p tcp -i eth0 --dport 80 -j REDIRECT
--to-port 8000
73. Reverse Proxy Sidecar Cache
Service 1
Service 2
v1
Service 2
v2
Service 1
Service 4
v1
Service 4
v2
Service 4
v3
Ruby
80. Reverse Proxy (Sidecar) Cache
Pros Cons
● Configuration-based (no
need to change
applications)
● Programming-language
agnostic
● Consistent with containers
and microservice world
● Difficult cache invalidation
● No mature solutions yet
● Protocol-based (e.g. works
only with HTTP)