Wednesday, September 15, 2021

Wasp sting infection | Antibiotics 7 days, 6 hour/ pill, Cephalexin

Sept. 15, 2021

Introduction

I went to Joyce station walk-in clinics this morning, and then the doctor gave me Cephalexin for my wasp sting on my hand. 

Learn quickly | Cephalexin 

头孢氨苄[编辑]

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头孢氨苄
Cefalexin Structual Formula V1.svg
Cefalexin ball-and-stick.png
系统(IUPAC)命名名称
IUPAC_name = (6R,7R)-3-甲基-7-[(R)-2-氨基-2-苯乙酰氨基]-8-氧代-5-硫杂-1-氮杂双环[4.2.0]辛-2-烯-2-甲酸
(7R)-3-Methyl-7- (α- D -phenylglycylamino) -3-cephem-4-carboxylic acid monohydrate
临床数据
读音/ˌsɛfəˈlɛksɪn/
商品名Keflex, Cepol, Ceporexine, Ceporex[1]
Drugs.comMonograph
MedlinePlusa682733
医疗法规
妊娠分级
  • AU: A
  • US: B (非人类研究中表明无风险)
给药途径口服
合法状态
合法状态
药代动力学数据
生物利用度吸收良好
蛋白结合度15%
代谢80% excreted unchanged in urine within 6 hours of administration
生物半衰期For an adult with normal renal function, the serum half-life is 0.5–1.2 hours[2]
排泄肾
识别信息
CAS注册号15686-71-2  ✓
ATC代码J01DB01 QJ51DB01
PubChemCID 2666
IUPHAR/BPS4832
DrugBankDB00567 ✓
ChemSpider25541 ✓
UNII5SFF1W6677 ✓
KEGGD00263 ✓
ChEBICHEBI:3534 ✓
ChEMBLCHEMBL1727 ✓
化学信息
化学式C16H17N3O4S
摩尔质量347.39 g/mol
物理性质
熔点326.8 °C(620.2 °F)

头孢氨苄(英语:Cefalexin或英语:Cephalexin,又译先锋霉素Ⅳ、又作赐福力欣、头孢力欣、赐尔复新、西华烈信、施华林、喜化幸、雪华力欣、或赐泛立信等[3])。是一种半合成的第一代口服头孢霉素类类抗生素药物,可用于数种细菌感染的抗生素。头孢氨苄是口服药,借由干扰细菌细胞壁的合成来杀死革兰氏阳性菌和部分革兰氏阴性菌[4]。头孢氨苄属于第一代头孢菌素,它与其他同类的抗生素如静脉施打的头孢唑啉具有相似的作用[5]。

头孢氨苄被以于治疗中耳炎、链球菌性咽炎、肺炎、骨与关节感染、蜂窝性组织炎、以及泌尿道感染等,它也可以被用于预防感染性心内膜炎。头孢氨苄对于抗药性金黄色葡萄球菌没有效果。头孢氨苄可以使用在对青霉素有轻微至普通程度过敏反应的病人身上,但对于有强烈过敏反应的病人而言则不适合使用。头孢氨苄对病毒感染并没有效果[4]。在台湾,由于组织穿透性不佳以及抗药性菌株较多,除蜂窝性组织炎及经确认菌株无抗药性的泌尿道感染[6]仍使用头孢氨苄作首选治疗药物,上述其他病症(中耳炎[7]、咽炎[8]、肺炎[9]、骨与关节感染[10]、以及感染心内膜炎[11])已经建议使用其他抗生素治疗[12][13]。

头孢氨苄的可能副作用包括过敏、肠胃不适、伪膜性结肠炎等等[4]。对于孕妇而言,本药品在许多孕妇使用后仍没有证据显示它会对孕妇或胎儿造成伤害[4][14](等同于美国的怀孕用药等级B;与澳洲的等级A),在哺乳期间使用本药品也是安全的[15]。儿童与65岁以上的老人都可以安全的使用本药。肾功能不佳的病人在使用本药品时应依指示减少剂量[4]。

2012年时头孢氨苄名列美国前百大最常使用药物[16],在澳洲则跻身前十五强[17]。它在1969-1970年间由葛兰素史克与礼来发现,并分别以Keflex与Ceporex为名上市[1][18]。今日,市面上已经有许多本药品的学名药可供选择,价格也不昂贵[4][19]。本品列名于世界卫生组织基本药物标准清单上,这张清单列出世界卫生组织建议医疗系统中应有的最重要的药物[20]。

适应症[编辑]

头孢氨苄可用于治疗敏感菌所致呼吸道(包括鼻窦炎、中耳炎、咽炎、扁桃体炎及肺炎)、泌尿道、皮肤及软组织、生殖器官等部位感染的治疗。抗菌谱与头孢噻吩、头孢噻啶基本相同,但抗菌效力比两者要弱。

用法及用量[编辑]

成人通常每6小时服250毫克或每8至12小时服500毫克,儿童用量通常以每日每公斤体重服25毫克计,分多次服用。如症状严重,医生可根据病人情况增加剂量。通常服7至10日,或依医生指示。

不良反应[编辑]

有些人服药后出现了不良反应,以下是一些较为常见者:

注意事项[编辑]

对头孢菌素过敏者、卟啉症(Porphyria)患者禁用头孢氨苄及其它头孢菌素。

对盘尼西林类抗生素过敏者、肾功能不全者、孕妇或授乳妇女应小心使用头孢氨苄及其它头孢菌素。对盘尼西林类抗生素过敏者中,大约10%的人也会对头孢菌素产生过敏反应。

外部链接[编辑]

Google Cloud networking in depth: Cloud Load Balancing deconstructed | 20 minutes reading

Sept. 15, 2021

Here is the link. 

Google has eight services that serve over one billion users every day. To offer the best availability and user experience for these services, we at Google engineered load-balancing infrastructure that scales on demand, utilizes resources efficiently, is secure and optimized for latency. This same load-balancing infrastructure is what we provide to you for your applications, in the form of the Google Cloud Load Balancing family. Unlike traditional load-balancing solutions, each of our load-balancing solutions are designed as large-scale distributed software-defined systems that scale-out and are highly resilient.

In this blog we will cover our portfolio of load-balancing offerings. We will start with our internet-facing load balancers that deliver Google’s massive edge-as-a-service to you via Network Load Balancing and Global Load Balancing. We’ll present benefits of container-native load balancing and show you how to secure the edge and optimize for latency and cost. Since many of you have services that are internal to Google Cloud, we’ll then cover your Internal Load Balancing options. We will wrap up by showing you how we can help you grow your cloud footprint and manage multi-cloud and heterogeneous services with internal layer-7 load balancing and Traffic Director for global service mesh.

Maglev for fast and reliable Network Load Balancing
For load-balancing external layer-4 TCP/UDP traffic, we offer Network Load Balancing built using our Maglevs. In production since 2008, Maglevs load balance all traffic that comes into our data centers, and distribute traffic to front-end engines at our network edges. The layer-4 traffic is distributed to a set of regional backend instances using a 5-tuple hash consisting of the source and destination IP address, protocol and source and destination port.

Diagram 1 



Maglev was a break from traditional load balancers in that it is software-based and operates in an active-active scale-out architecture. With Maglev Consistent Hashing, Maglev-based load balancers evenly distribute traffic over hundreds of backends as well as minimize the negative impact of unexpected faults on connection-oriented protocols. Network Load Balancing is a great solution for lightweight L4-based load balancing where you want to preserve the client IP address all the way to the backend instance and also perform TLS termination on these instances.

Global Load Balancing for a single VIP, global reach
For our global load-balancing solution, we pushed load balancing to the edge of Google’s global network to front end the global load-balancing capacity behind a single Anycast Virtual IPv4 or IPv6 address. You can deploy capacity in multiple regions without having to modify the DNS entries or add new load balancer front-end IP address (VIPs) for new regions. You don’t have to deal with the challenges of traditional DNS-based load balancers such as clients caching IP addresses or regional siloed resources resulting in sub-optimal load balancing and utilization of backends instances.

Diagram 2


With global load balancing, you get cross-region failover and overflow. Global LB’s traffic distribution algorithm automatically directs traffic to the next closest instance with available capacity in the event of failure of or lack of capacity for instances in the region closest to end user.  

Global LB delivers first class support for both VMs and containers. For containers, we built an abstraction called Network Endpoint Groups (NEG), which is essentially a group of IP address and port pairs. NEGs enable you to directly specify a container endpoint as opposed to first directing traffic to the node on which it resides and then redirecting to the container using kube-proxy. As a result, you can deliver lower latency, greater throughput and higher fidelity health checks for your services using NEGs.

Secure the edge
To secure your service, we recommend taking a defense-in-depth approach. We also recommend that you deploy TLS for data privacy and integrity purposes. We do not charge extra for encrypted vs. unencrypted traffic. We offer HTTPS and SSL proxy in our global load-balancing family. We also offer Managed Certificates to reduce the work of procuring certs and managing their lifecycle. With SSL policies you can specify the minimum TLS version and SSL features that you wish to enable on your HTTP(S) and SSL proxy load balancers. We also offer multiple pre-configured profiles, including a custom one that lets you allows specify the ciphers and SSL features you want to use.

With Google’s global network and global load-balancing, Google is able to mitigate and dissipate layer-3 and layer-4 volumetric attacks. To protect against application layer attacks, we recommend using Cloud Armor attached to your Global HTTP(S) load balancer. Use this in concert with Identity Aware Proxy to authenticate users and authorize access to your backend services.

Optimize for latency and cost

Make the web faster
We spend a lot of time at Google working to make the web faster. QUIC is a UDP-based encrypted transport optimized for HTTPS and HTTP/2 is foundational for gRPC support. Google cloud load balancing supports QUIC traffic to the load balancer and supports multiplexed streams of HTTP/2 to the load balancer, followed by load balancing these multiple HTTP/2 streams to the backend.

Google Cloud CDN runs on our globally distributed edge points, so you can reduce network latency when serving website content, offload content origins and reduce serving costs. Just set up HTTP(S) Load Balancing and then enable CDN by clicking a single checkbox.

Optimize for performance or cost with Network Tiers
With Network Tiers, you can optimize your workload for performance with Premium Tier, which takes advantage of Google’s performant network, or optimize for cost with Standard Tier, where your return traffic travels over regular ISP networks like other public clouds but incurs lower egress costs.

Internal Load Balancing for private services
Many Google Cloud customers have private workloads that need to be protected from the public internet. Those services need to scale and grow behind a private VIP that is accessible only by internal instances. For such users we offer regional layer-4 Internal Load Balancing based on our Andromeda network virtualization stack. Similar to our HTTP(S) Load Balancer and Network Load Balancer, Internal L4 Load Balancing is neither a hardware appliance nor an instance-based solution, and can support as many connections per second as you need since there’s no load balancer in the path between your client and backend instances.

Diagram 3



What’s next?
For business agility, many organizations are transitioning from monolithic applications to microservices, looking for a uniform way to create and manage heterogenous and multi-cloud services with security, observability and resiliency. This is where service mesh comes in, providing software-defined networking (SDN) for services, including load balancing. With service mesh, networking complexity is abstracted away to the service mesh’s data-plane, which is implemented as a service proxy such as Envoy, leaving you free to focus on building business logic. Envoy is a performant, feature-rich and open-source service mesh data plane that you can configure and manage via the service mesh’s control plane (such as Istio). Google is a key contributor to both the Envoy and Istio open-source initiatives.

Diagram 4




We recently launched Traffic Director, a GCP-managed traffic management control plane for service mesh. Traffic Director communicates with the service proxies in the data plane using open-source xDS APIs to enable global load balancing, scalable health checking, autoscaling, resiliency and policy-driven traffic steering.

Learn more
To learn more about Cloud Load Balancing, start with the Next ‘19 talks on Google Cloud Load Balancing Deep Dive and Best Practices, Traffic Director and Envoy-based ILB for Production Grade Service Mesh & Istio and read the documentation. We’d love your feedback on these features and what else you’d like to see from our load balancing portfolio. You  can reach us at gcp-networking@google.com.

Maglev: The Load Balancer behind Google’s Infrastructure (Architectural Overview)— Part 1/3 | Google load balancer | Network layer balancer

 Sept. 15, 2021

Here is the article. 

My notes:

The man in the middle intelligently shuffling all the traffic to the appropriate backend is Maglev, the name for Google’s Distributed Load Balancer (LB).

In order to cover this beast that is Maglev, I have opted to break it down into 3 separate articles that build on each other.
Article 1 (this article): looks to give an overview of Maglev and fundamental components of its architecture.
Article 2: Will take a look inside Maglev in particular how the forwarder works.
Article 3: The novel and intelligent implementations that have made Maglev so successful.


Maglev: A Fast and Reliable Software Network Load Balancer | Paper reading is my favorite | 20+ minutes to read

 Maglev is Google’s network load balancer. It is a large distributed software system that runs on commodity Linux servers. Unlike traditional hardware network load balancers, it does not require a specialized physical rack deployment, and its capacity can be easily adjusted by adding or removing servers. Network routers distribute packets evenly to the Maglev machines via Equal Cost Multipath (ECMP); each Maglev machine then matches the packets to their corresponding services and spreads them evenly to the service endpoints. To accommodate high and ever-increasing traffic, Maglev is specifically optimized for packet processing performance. A single Maglev machine is able to saturate a 10Gbps link with small packets. Maglev is also equipped with consistent hashing and connection tracking features, to minimize the negative impact of unexpected faults and failures on connection-oriented protocols. Maglev has been serving Google's traffic since 2008. It has sustained the rapid global growth of Google services, and it also provides network load balancing for Google Cloud Platform.

Here is the paper.

Abstract 

Maglev is Google’s network load balancer. It is a large distributed software system that runs on commodity Linux servers. Unlike traditional hardware network load balancers, it does not require a specialized physical rack deployment, and its capacity can be easily adjusted by adding or removing servers. Network routers distribute packets evenly to the Maglev machines via Equal Cost Multipath (ECMP); each Maglev machine then matches the packets to their corresponding services and spreads them evenly to the service endpoints. To accommodate high and ever-increasing traffic, Maglev is specifically optimized for packet processing performance. A single Maglev machine is able to saturate a 10Gbps link with small packets. Maglev is also equipped with consistent hashing and connection tracking features, to minimize the negative impact of unexpected faults and failures on connection-oriented protocols. Maglev has been serving Google’s traffic since 2008. It has sustained the rapid global growth of Google services, and it also provides network load balancing for Google Cloud Platform.